August 2020 - Comp-neuro - lists.cnsorg.org

Up to 6 PhD fellowships in Cognitive Neuroscience at SISSA, Trieste, Italy, to start Oct, 2020
by Alessandro Treves Oct. 12, 2022

Oct. 12, 2022

SISSA is an elite postgraduate research institution located in Trieste, Italy, and focused on Maths, Physics and Neuroscience. It operates in English: many among its students and faculty are not Italian. The Cognitive Neuroscience Department hosts 6 research labs that study the neuronal bases of time and magnitude processing, visual perception, motivation and intelligence, language and reading, tactile perception and learning, and neural computation. The Department is very inter–disciplinary; our approaches include behavioural, psychophysics, and neurophysiological experiments with humans and animals, as well as computational and mathematical models. Students with diverse backgrounds (physics, math, medicine, psychology, biology) are most welcome to apply. The Department has an exceptional track record with highly competitive funds (recent funding includes 4 ERC and 3 Human Frontiers grants) and publication in top journals (Nature, Science, PNAS, Current Biology). Recent placements after PhD include Harvard, MIT, Columbia and Princeton in the US; the NTNU, Manchester and Radboud in Europe; and Sydney University, Australia. Our alumni have been awarded 4 ERC grants, the 2015 Kandel Young Neuroscientist Prize and the 2017 ICTP Prize. More information about the Department is available at our website https://phdcns.sissa.it. The selection procedure is now open; to learn how to apply, please visit https://phdcns.sissa.it/admission-procedure. Please contact the PhD Coordinator (davide.crepaldi(a)sissa.it) and/or your prospective supervisor for more information and informal enquiries. -- Alessandro Treves SISSA, Cognitive Neuroscience, http://people.sissa.it/~ale/limbo.html if in, rm 241, via Bonomea 265, 34136 Trieste, Italy: +39-040-3787623

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Postdoc in neural data analysis
by Mark Humphries June 26, 2022

June 26, 2022

A 3 year postdoc post is available in the lab of Prof Mark Humphries, at the University of Nottingham (UK) In this project, our aim is to test the overarching hypothesis that movement transitions are encoded by the same neural population reconfiguring its joint activity, for both rhythmic and discrete movements. We will tackle this question using newly-available population recordings during rhythmic movement transitions in Aplysia and discrete arm movement transitions in monkeys, The Humphries’ group researches fundamental insights into how the joint activity of neurons encodes information about and actions in the world. For more see: https://www.humphries-lab.org Queries: mark.humphries(a)nottingham.ac.uk Deadline: 5th September Full details, and to apply: https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2 [http://jobs.nottingham.ac.uk/org/images/socialmedia.png]<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Job Vacancy at the University of Nottingham: Research Associate/Fellow (Fixed term)<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Applications are invited for a postdoctoral research fellow to join the Humphries’ group on the MRC-funded project “Uncovering the neural basis of movement transitions”. The Humphries’ group researches fundamental... jobs.nottingham.ac.uk Professor Mark Humphries | MRC Senior non-Clinical Fellow | Chair in Computational Neuroscience Lab: humphries-lab.org<https://www.humphries-lab.org/> Twitter: @markdhumphries Public blog: https://medium.com/the-spike This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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Explainable AI: Overcoming problems of Deep Learning problems with Adaptive Resonance
by Grossberg, Stephen April 9, 2022

April 9, 2022

Dear Colleagues, There's currently a lot of interest in AI, notably Deep Learning, and in achieving autonomous adaptive intelligence. The following new article summarizes foundational problems of reliability and trustworthiness of Deep Learning, explains how Adaptive Resonance overcomes them, and outlines a blueprint for achieving autonomous adaptive intelligence: Grossberg, S. (2020). A path towards Explainable AI and autonomous adaptive intelligence: Deep Learning, Adaptive Resonance, and models of perception, emotion, and action. Frontiers in Neurobotics, June 25, 2020. https://doi.org/10.3389/fnbot.2020.00036 Best, Steve Grossberg

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Postdoc at the University of Leicester to work on human single cell recordings
by Quian Quiroga, Rodrigo (Prof.) Nov. 23, 2021

Nov. 23, 2021

The Centre for Systems Neuroscience at the University of Leicester, UK, offers a 3-years postdoc position to study single cell recordings in humans – performed in epileptic patients for curative surgery. The project will investigate concept cells (a.k.a. Jennifer Aniston neurons) – that means, neurons in the hippocampus and surrounding areas that selectively fire to specific concepts, like different pictures and the written or spoken name of a particular person (e.g. Quian Quiroga et al, Nature 2005; Quian Quiroga Nature Reviews Neuroscience 2012), which are involved in declarative memory functions. For more details see: www.le.ac.uk/csn The successful candidate will contribute to performing recordings with patients in collaborating hospitals and the analysis of the data to investigate the role of these neurons in memory. He/She should have very good quantitative skills (data processing, and programing e.g. in Matlab) and a strong background or interest in neuroscience. He/She should be able to work both independently and as part of a research team within the Centre for System Neuroscience at Leicester and with our external collaborators. Informal enquiries are welcome and should be made to Paula Warrington, Research Centre Manager, csn(a)le.ac.uk or 0116 252 3249. To apply, please use this link: https://jobs.le.ac.uk/vacancies/1393/research-associate.html The applications should include a curriculum vitae and a brief description of their scientific interests The closing date for the applications is 21st October 2019. Cheers, Rodrigo Rodrigo Quian Quiroga Centre for Systems Neuroscience University of Leicester www.le.ac.uk/csn

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Postdoc (3 yrs) in dynamical reconfigurations of neural populations during movement
by Mark Humphries March 9, 2021

March 9, 2021

A 3 year postdoc post is available in the lab of Prof Mark Humphries, at the University of Nottingham (UK) In this project, our aim is to test the overarching hypothesis that movement transitions are encoded by the same neural population reconfiguring its joint activity, for both rhythmic and discrete movements. We will tackle this question by developing new computational algorithms for dynamic systems, and applying them to newly-available population recordings during rhythmic movement transitions in Aplysia and discrete arm movement transitions in monkeys, The Humphries’ group researches fundamental insights into how the joint activity of neurons encodes information about and actions in the world. For more see: https://www.humphries-lab.org Queries: mark.humphries(a)nottingham.ac.uk Deadline: 10th January 2020 Full details, and to apply: https://www.nottingham.ac.uk/jobs/currentvacancies/ref/SCI182819X1 Professor Mark Humphries | MRC Senior non-Clinical Fellow | Chair in Computational Neuroscience Lab: humphries-lab.org<https://www.humphries-lab.org/> Twitter: @markdhumphries Public blog: https://medium.com/the-spike This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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Announcing the 1st Brain-Computer Interface Un-Conference (BCI-UC)
by Moritz Grosse-Wentrup Feb. 5, 2021

Feb. 5, 2021

Dear Colleagues: We cordially invite you to the 1st Brain-Computer Interface Un-Conference (BCI-UC)! https://bciunconference.univie.ac.at/ The 1st BCI-UC is an entirely virtual event that takes place on July 23rd 2020 from 3 pm to 9:30 pm (CEST). It differs in various ways from traditional conferences in our field: * All presentations are publicly streamed via Crowdcast. * Anybody can apply for a presentation slot by submitting an abstract. All registered attendees can up-vote their favorite abstracts. In this way, the whole community decides which presentations they would like to see presented at the conference. * Voting commences on Monday, June 29th at 8 am (CEST) and ends on Thursday, July 16th at 12 midnight (CEST). The authors of the top-rated abstracts are invited to present their work at the conference. * Registration (free of charge) is required for submitting an abstract and to up-vote submissions. In addition to the contributed talks, the 1st BCI Un-Conference features two keynotes presentations: 1. Mariska J Vansteensel (UMC Utrecht Brain Center): Towards the Daily Life Implementation of ECoG-BCIs 2. Christian Herff (Maastricht University): Decoding Speech from Invasive EEG Please join us in exploring this new way of disseminating research in our community! The BCI-UC Organizing Committee: Moritz Grosse-Wentrup Anja Meunier Philipp Raggam Anita Resch Jiachen Xu -- Univ.-Prof. Dr.-Ing. Moritz Grosse-Wentrup Research Group Neuroinformatics Faculty of Computer Science University of Vienna Hörlgasse 6, A-1090 Wien, Austria moritz.grosse-wentrup(a)univie.ac.at +43-1-4277-79610 http://neural.engineering/

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Funded PhD and Data scientist positions
by Abhishek Banerjee Jan. 14, 2021

Jan. 14, 2021

Dear colleagues, Two funded *Ph.D. positions* are available in the newly established Adaptive Decision-making lab as a part of Neuroscience, Neurodisability and Neurological Disorders research theme, Biosciences Institute, Newcastle University, UK. The research carried out as part of th Ph.D fellowship will investigate the role of behaviourally relevant neural circuits in decision-making and its dysfunctions in neurological disorders using experimental and theoretical approaches (PNAS 2016; BRAIN 2019; bioRxiv 2020). Exciting local and international collaborations will ensure a high standard of training and mentorship. The position is funded (UK/EU rate) for up to 3.5 years and the application deadline is *6th January 2020*. Application details can be found here or by email provided below: https://www.findaphd.com/phds/project/mrc-dimen-doctoral-training-partnersh… . Additionally, the Banerjee Lab is also hiring a *Data Scientist* to be involved in projects that focus on understanding cortical computation during behaviour by combining large-scale recordings and imaging of neuronal populations. This person will be involved in analysing experimental data, developing software tools, and helping with data infrastructure. The application deadline is *31st January 2020*. Qualifications for the Data scientist position: - M.Sc. degree (or exceptional B.Sc.) in Physics, Computer Science, Mathematics, Engineering, or related technical field. - Programming experience in MATLAB is required, and additional experience in Python and LABView is preferred. - Background in computational neuroscience, image analysis, or machine learning is a plus. For informal inquiry, or if interested in applying for the Data scientist position, please submit a CV along with names of 3 referees to: Dr. Abhi Banerjee <abhi.banerjee(a)newcastle.ac.uk>. More details here: https://loop.frontiersin.org/people/11499/overview and http://neuronic.mit.edu/ Best wishes, Abhi -- Abhishek Banerjee Senior Lecturer Head, Adaptive Decision-making Lab Biosciences Institute Newcastle University United Kingdom I neuronic.mit.edu Skype: amiappu I @abhii_mit

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Creating a list of important computational predictions
by Yiota Poirazi Jan. 4, 2021

Jan. 4, 2021

Dear all, I believe you would agree that, the greatest recognition of our computational work comes with the experimental verification of our computational predictions. To highlight the most important outcomes of our theoretical work and facilitate a closer interaction with experimental labs so as to increase the chances of our predictions being experimentally tested, I would like to encourage you to nominate your favorite prediction at the following google form: https://docs.google.com/forms/d/e/1FAIpQLSeJZ2RrXJ0nZonIuyNzN0Cl gXDKDb7xTzoJOiqZTGxm9Kh7ow/viewform?c=0&w=1&usp=mail_form_link This effort started during the CNS 2017 meeting in Antwerp with the support of the OCNS Board. The resulting list will be posted on the CNS 2017 web site and disseminated in social media, as a reference for experimentalists. Thank you very much for supporting this important effort! Best wishes, Yiota Poirazi -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/> -- This message has been scanned for viruses and dangerous content by *E.F.A. Project* <http://www.efa-project.org>, and is believed to be clean. Click here to report this message as spam. <http://mailgate1.imbb.forth.gr/cgi-bin/learn-msg.cgi?id=4BCD7A00A1.A57D7&to…> -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/>

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ANDA 2020 - G-Node Advanced Neural Data Analysis Course, April 14-30, 2020, Jülich, Germany
by Thomas Wachtler Dec. 23, 2020

Dec. 23, 2020

ANDA 2020 - G-NODE ADVANCED NEURAL DATA ANALYSIS COURSE April 14 - 30, 2020 Haus Overbach, Jülich-Barmen, Germany Techniques to record neuronal data from populations of neurons are rapidly improving. Simultaneous recordings from hundreds of channels are possible while animals perform complex behavioral tasks. The analysis of such massive and complex data becomes increasingly challenging. This advanced course aims at providing deeper training in state-of-the-art analysis approaches in systems neuroscience. The course is addressed to excellent master and PhD students and young researchers who are interested in learning advanced techniques in data analytics and in getting hands-on experience in the analysis of electrophysiological data. Internationally renowned researchers will give lectures on statistical data analysis and data mining methods with accompanying exercises. Students will define and perform their own analyses on provided data to solve a challenge. Participants are required to have a strong interest in data analysis, a background in a mathematical or related field, knowledge of algebra, matrix operations, and statistics, and need to have solid programming experience (preferably in Python). FACULTY · Moshe Abeles, Hebrew Univ. Jerusalem, Israel · Michael Denker, Jülich Research Center, Germany · Udo Ernst, Univ. Bremen, Germany · Sonja Grün, Jülich Research Center, Germany · Adam Kohn, Albert Einstein College of Medicine, New York, USA · Jakob Macke, TU Munich, Germany · Luca Mazzucato, Univ. of Oregon, Eugene, USA · Martin Nawrot, Univ. of Cologne, Germany · Yifat Prut, Hebrew Univ. Jerusalem, Israel · Hansjörg Scherberger, German Primate Center, Göttingen, Germany · Thomas Wachtler, LMU Munich, Germany TOPICS COVERED Single neuron properties and statistics · Stochastic processes · Surrogate methods · Detection of spatio-temporal patterns · Unitary Events · Statistical analysis of massively parallel spike data · Higher-order correlation analyses · Elephant toolbox · Spike-LFP relationship · Population coding · State space analysis · Machine learning · Data mining · Research data management and reproducibility REQUIREMENTS Applicants should be familiar with linear algebra, probability, differential and integral calculus and experienced using Python or Matlab. Preparatory reading material will be provided. Students should bring their own laptops and should be able to install software on their system. Students that do not have a suitable laptop should indicate this immediately after acceptance to the course. We will be able to provide a small number of laptops for the time of the course. COURSE FEE A course fee of 1000 Euros will be charged to cover costs for accommodation and meals. Limited financial support may be available for students that otherwise would not be able to attend, which is to be indicated in the application. HOUSING Accommodation in 2-bed rooms for students will be provided at the course site. HOW TO APPLY The application should include · a letter of motivation (max 1 page) · curriculum vitae (please indicate the relevant courses you have taken) · description of programming experience · a letter of recommendation. Please send all documents as a single PDF file to <advanced-course(a)g-node.org>. APPLICATION DEADLINE Applications must be received by NOVEMBER 15, 2019. Early application is encouraged. For further information see http://www.g-node.org/anda

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SMILES virtual workshop @ICDL 2020
by Xavier Hinaut Oct. 28, 2020

Oct. 28, 2020

The SMILES (Sensorimotor Interaction, Language and Embodiment of Symbols) Workshop will take place virtually at the ICDL 2020 (International Conference on Developmental Learning). * Call for abstracts and papers: - Deadline: 25th of September 2020 - papers abstracts: 2 pages - long papers: 4-6 pages - Submissions: smiles.conf(a)gmail.com <mailto:smiles.conf@gmail.com> - Papers format: same as ICDL conference https://cis.ieee.org/publications/t-cognitive-and-developmental-systems/tcd… <https://cis.ieee.org/publications/t-cognitive-and-developmental-systems/tcd…> - Workshop dates (coming soon): the days before or after the ICDL conference (26-30 October 2020) * Workshop Short Description On the one hand, models of sensorimotor interaction are embodied in the environment and in the interaction with other agents. On the other hand, recent Deep Learning development of Natural Language Processing (NLP) models allow to capture increasing language complexity (e.g. compositional representations, word embedding, long term dependencies). However, those NLP models are disembodied in the sense that they are learned from static datasets of text or speech. How can we bridge the gap from low-level sensorimotor interaction to high-level compositional symbolic communication? The SMILES workshop will address this issue through -an interdisciplinary approach involving researchers from (but not limited to): - Sensori-motor learning, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Sensori-motor learning, - Symbol grounding and symbol emergence, - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and acquisition in brains and machines, - Models of animal communication, - Understanding composition and temporal processing in neural network models, and - Enaction, active perception, perception-action loop. * More info - contact: smiles.conf(a)gmail.com <mailto:smiles.conf@gmail.com> - organizers: Xavier Hinaut, Clement Moulin-Frier, Silvia Pagliarini, Joni Zhong, Loo CHU KIONG, Michael Spranger, Tadahiro Taniguchi - invited speakers (coming soon) - workshop website (comming soon): https://sites.google.com/view/smiles-workshop/ <https://sites.google.com/view/smiles-workshop/> - ICDL conference website: https://cdstc.gitlab.io/icdl-2020/ <https://cdstc.gitlab.io/icdl-2020/> * Workshop Long Description Recently Deep Learning networks have broken many benchmarks in Natural Language Processing (NLP), e.g. [1]. Such breakthroughs are realized by a few mechanisms (e.g. continuous representations like word embedding, attention mechanism, ...). However, no equivalent finding happened towards the understanding of which mechanisms enable the brain to perform similar functions. Deep Learning does not reproduce learning mechanisms nor the dynamics of the brain. The brain needs to parse incoming stimuli and learn from them incrementally, it cannot unfold time like deep learning algorithms such as Back-propagation through time (BPTT). Thus, we still lack the key neuronal mechanisms needed to properly model the (hierarchies of) functions in language perception and production. Other models of language processing reproducing the behavior of brain dynamics (Event-Related-Potentials (ERPs) [2] or functional Magnetic Resonance Imaging (fMRI) [3]) have been developed. However, such model softens lack explanatory power demonstrating the causes of such observed dynamics: i.e. what is computed and why is it computed – for which purpose? We need more biologically plausible learning mechanisms while producing causal explanations of the experimental data modelled. There is converging evidence that language production and comprehension are not separated processes in a modular mind, they are rather interwoven, and this interweaving is what enables people to predict themselves and each other [4].Interweaving of action and perception is important because it allows a learning agent (or a baby) to learn from its own actions: for instance, by learning the perceptual consequences(e.g. the heard sounds) of its own actions (e.g. vocal productions) during babbling [5]. Thus, the agent learns in a self-supervised way instead of relying only on supervised learning, which in contrast, imply non-biological teacher signals cleverly designed by the modeler. Explicit neuronal models explaining which are the mechanisms shaping these perceptuo-motor units through development are missing. The existence of sensorimotor (i.e. mirror) neurons at abstract representation levels (often called action-perception circuits [6]), jointly with the perceptuo-motor shaping of sensorimotor gestures [5], suggest the existence of similar action-perception mechanisms implemented at different levels of hierarchy. How could we go towards such hierarchical architectures based on action-perception mechanisms? Importantly, a language processing model needs a way to acquire the semantics of the (symbolic) perceptuo-motor gestures and of the more abstract representations, otherwise it would consider only morphosyntactic and prosodic featuresof language. These symbolic gestures, i.e. signs, need to be grounded to the mental concept, i.e. signified, they are representing. Several theories and robotic experiments give examples of how symbols could be grounded or how symbols could emerge [7]. However, current neurocomputational models aiming to explain brain processes are not grounded. Robotics have an important role here for the grounding of semantics by experiencing the world through interactions with the physical world and with humans. We need mechanisms that start from raw sensory perception and raw motor commands in order to let emerge plausible representations through development, instead of arbitrary representations. Finally, computational models of emergent communication in agent populations are currently gaining interest in the machine learning community [8], [9]. These contributions show how a communication system can emerge to solve cooperative tasks in sequential environments. However, they are still relatively disconnected from the earlier theoretical and computational literature aiming at understanding how language might have emerged from a prelinguistic substance [10], [11]. We need to conceive communication as the emergent result of a collective behavior optimization process and to ground the resulting computational models into the theoretical literature from language evolution research. The SMILES workshop will aim at discussing each of the questions mentioned above, together with original approaches on how to integrate them. [1] J. Devlin et al., 2018. [2] H. Brouwer and J. C. J. Hoeks, 2013. [3] M. Garagnani et al. 2008. [4] M. J. Pickering and S. Garrod, 2013. [5] J.-L. Schwartz et al., 2012. [6] F. Pulvermüller and L. Fadiga, 2010. [7] T. Taniguchi et al., 2016. [8] S. Sukhbaatar et al.,2016. [9] I. Mordatch and P. Abbeel, 2017. [10] M. Tomasello et al., 2005. [11] P.-Y. Oudeyer and L. Smith, 2015. Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Université de Bordeaux Institut des Maladies Neurodégénératives +33 5 33 51 48 01 www.xavierhinaut.com

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Lecture video about brain mechanisms that cause mental disorders
by Grossberg, Stephen Oct. 17, 2020

Oct. 17, 2020

Dear Colleagues, I gave a pre-recorded keynote lecture on Zoom to the World Congress on Computational Intelligence on July 22 about how particular brain dysfunctions can cause symptoms of mental disorders like Alzheimer's disease, autism, amnesia, and neglect: http://sites.bu.edu/steveg/files/2020/07/Grossberg-WCCI-keynote-Glasgow-vid… The lecture can also be found on my web page sites.bu.edu/steveg along with a pdf of its powerpoint slides. Best, Steve Grossberg Stephen Grossberg http://en.wikipedia.org/wiki/Stephen_Grossberg http://scholar.google.com/citations?user=3BIV70wAAAAJ&hl=en https://youtu.be/9n5AnvFur7I https://www.youtube.com/watch?v=_hBye6JQCh4 Wang Professor of Cognitive and Neural Systems Director, Center for Adaptive Systems Professor Emeritus of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering Boston University sites.bu.edu/steveg steve(a)bu.edu

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NEURAL COMPUTATION - February 1, 2020
by Terry Sejnowski Oct. 2, 2020

Oct. 2, 2020

Neural Computation - Volume 32, Number 2 - February 1, 2020 Available online for download now: http://www.mitpressjournals.org/toc/neco/32/2 http://cognet.mit.edu/content/neural-computation ----- Article Face Representations via Tensorfaces of Various Complexities Sidney Lehky, Anh-Huy Phan, Andrzej Cichocki, and Keiji Tanaka Letters Transition Scale-spaces: A Computational Theory for the Discretized Entorhinal Cortex Nicolai Waniek From Synaptic Interactions to Collective Dynamics in Random Neuronal Networks Models: Critical Role of Eigenvectors and Transient Behavior Ewa Gudowska-Nowak, Maciej A Nowak, Dante Chialvo, Jeremi K Ochab, and Wojciech Mateusz Tarnowskic Synaptic Scaling Improves the Stability of Neural Mass Models Capable of Simulating Brain Plasticity Jure Demsar, Rob Forsyth Scaled Coupled Norms and Coupled Higher Order Tensor Completion Kishan wimalawarne, Makoto Yamada, and Hiroshi Mamitsuka Improving Generalization via Attribute Selection on Out-of-the-box Data Xiaofeng Xu, Ivor W. Tsang, and Chuancai Liu ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs(a)mit.edu ------------

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postdocs with Peter Dayan in Tübingen
by Peter Dayan Sept. 28, 2020

Sept. 28, 2020

Postdoc(s) in Neural Reinforcement Learning / Computational Psychiatry (m/f/d) 100% Peter Dayan is looking to hire one or more postdocs (100%) to work in the areas of neural reinforcement learning, computational neuromodulation, and computational psychiatry. These positions will start in the Faculty of Science, Department of Computer Science, University of Tübingen, as part of an Alexander-von-Humboldt Professorship award. There are also targeted positions on the computational anatomy of cortico-striatal connections (funded by a collaborative NIH grant with Professor Suzanne Haber) and with the International Brain Lab (a large collaboration with 20 other investigators, funded by the Simons Foundation). Peter Dayan has an affiliation with the University of Tübingen and the Max Planck Institute for Biological Cybernetics and collaboration is expected. The salary will be paid in accordance with the collective agreement for the public sector (salary at E13 TV-L, commensurate to experience and qualifications). The positions are available immediately, and are initially limited to two years (with the possibility of extension). Please direct scientific inquiries to dayan(a)tue.mpg.de and administrative inquiries to susan.fischer(a)tue.mpg.de. Responsibilities include: • Planning and carrying out research projects, for instance building theories and computational models of data from human and animal experiments, conducting experiments, analysing behavioural and neural data, writing and editing scientific papers/reports. • Helping to mentor and supervise student projects. • Participating in scientific conferences. • Helping to organize and conduct collaborations in Tübingen as well as nationally and internationally • Helping with building and running an effective academic lab environment at the intersection between the Max Planck Institute for Biological Cybernetics and the science and medical faculties at the University of Tübingen. The successful candidate(s) should have a PhD in computational neuroscience or related fields. Proficiency in a high level mathematical or statistically-oriented programming language such as python, R, Julia or matlab, and intimate familiarity with advanced data analysis are essential. The candidate(s) should be able to work independently and troubleshoot and should show good capacity and value for teamwork and communication skills. The University of Tübingen is one of the Excellence Universities in Germany. It is home to a vibrant research community, with very strong research activity in Neuroscience and Clinical Psychology / Psychiatry as well as Artificial Intelligence and Machine Learning. We offer an open research culture, where original thinking and academic merit are encouraged and nurtured, and encourage applications from all nationalities, backgrounds, and genders. The University of Tübingen is dedicated to increase the percentage of female employees in the field of science. Therefore, female candidates are strongly encouraged to apply. Applications should include a CV, a list of publications, summaries of scientific achievements and research plans, the position for which the application is intended, and the names and contact details of three referees. Applications should be sent in a single PDF to: susan.fischer(a)tue.mpg.de Applications arriving before June 30th 2020 will receive full consideration.

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PhD position: Machine learning to record and enhance sleep and lucid dreaming
by Martin Dresler Sept. 3, 2020

Sept. 3, 2020

Hi, Arenar B.V. and the Donders Institute offer a joint PhD position combining data science/AI and wearable EEG technology with sleep/dream research. In this project, the wearable sleep EEG headband iBand+ will be further developed and applied in several experimental studies. First, we will develop automatic sleep stage detection algorithms using machine learning strategies. We will then implement closed-loop acoustic stimulation procedures to enhance sleep slow oscillations to improve deep sleep. We will further develop combined acoustic and visual stimulation procedures which will allow to enhance self-awareness during sleep (i.e. lucid dreaming) and subsequent mood in the morning. The validity and efficacy of these procedures will be tested experimentally in large longitudinal studies in naturalistic home-based settings. The successful candidate will be centrally involved in the development, will lead different research projects within this general framework; will be closely involved in daily supervision of MSc students assisting the project; and will participate in the vibrant Donders Graduate School. Job details • 4 years at Donders, extension to permanent position at Arenar possible • Deadline: 31 August 2019 • Starting date: October/November, but somewhat flexible • Salary: starting with € 40000 gross per year Candidate profile • MSc-level background in Data Science, ML, AI, computer sciences, or adjacent field; • Proficiency in Python, C, C++, statistics • Interest in sleep, lucid dreaming, meditation • The capacity to participate in a collaborative, interdisciplinary, international research environment; • Fluency in written and spoken English. Candidates who only partially meet this profile are nonetheless strongly encouraged to apply! Organization The PhD project is a collaboration between Arenar B.V. and the Donders Institute. Arenar B.V. is a Dutch technology start-up based in Nijmegen, founded in 2016 by a team of engineers/developers with a combined technical industry experience exceeding 40 years working at leading technology companies such as NXP, Philips, Texas Instruments. Work in Arenar’s small enthusiastic team offers plenty of flexibility, responsibility and lots of influence on the product development. In particular, Arenar develops the iBand+ ( http://www.ibandplus.com) and many more upcoming innovative products. The project is embedded in the infrastructure of the Donders Centre for Cognitive Neuroimaging, providing a unique and stimulating learning environment for young researchers, including a high-profile graduate school and in-house methodological expert courses. Sleep research is a vibrant and rapidly growing field at the Donders Institute, with several new research groups in human and animal sleep research. The project is further embedded in the Radboud University Medical Center. Radboud UMC strives to be a leading developer of sustainable, innovative and affordable healthcare to improve the health and wellbeing of people and society in the Netherlands and beyond. Application Please apply with a brief motivation letter explaining your interest and qualifications regarding the position, your prior research/work experience, a CV, and contact information of two professional references: https://www.radboudumc.nl/en/vacancies/70061-phd-candidate-machine-learning… For specific questions about this position, please contact martin.dresler(a)donders.ru.nl Cheers, Martin -- Donders Sleep & Memory Lab, Radboud University Medical Center Kapittelweg 29, 6525 EN Nijmegen, Netherlands https://dreslerlab.org

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NeuTouch Summer School
by Miguel Casal Santiago Aug. 31, 2020

Aug. 31, 2020

The Horizon 2020 project Neutouch is glad to announce that the first summer school of the project about “Touch for prosthetics” will be held online the 21 & 28 September and 5 & 12 October 2020. The school will have talks from cutting-edge professors and students in the field of touch, including topics such as neuromorphic engineering, brain-computer interfaces, computational neuroscience and machine learning, among others. We invite you to take a look at the program together with a small description of the talks in this link <https://www.neutouch.eu/events/neuschool20>, where you can also subscribe for free. You can contact neutouchboard(a)gmail.com <mailto:neutouchboard@gmail.com> for doubts and requests Neutouch Editorial Board

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Postdoc positions in Aarhus University, Denmark
by Diego Vidaurre Aug. 30, 2020

Aug. 30, 2020

Dear all, Funded by an ERC grant, I am opening two postdoc positions in my lab in Aarhus University in collaboration with Oxford University, to develop new methods on machine learning and Bayesian time series modelling, with application to specific problems in computational neuroscience. If someone is interested, or know of someone interested, please get in contact. More details on the topics, salary, conditions, requirements, etc. here: https://health.au.dk/en/about-health/vacant-positions/job/postdoc-in-integr… Thanks Diego Vidaurre

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Postdoc in computational cognitive neuroscience of speech processing at the University of Texas at Austin (USA)
by Hamilton, Liberty Aug. 29, 2020

Aug. 29, 2020

The Hamilton Lab at The University of Texas at Austin seeks to hire a full-time postdoctoral fellow to study brain processing of natural speech in the presence of noise. Our approaches include computational methods (neural networks, linear/nonlinear regression models, encoding/decoding), electrophysiology (scalp EEG and intracranial EEG), and fMRI. A postdoc is sought for a one-year contract to begin a collaborative project with the Huth Lab on brain processing of natural sounds using scalp EEG and fMRI. Lab websites: https://slhs.utexas.edu/research/hamilton-lab and https://cs.utexas.edu/~huth/ Start date: Open Full time, benefits eligible, one-year contract with potential for extension based on performance/funding. Qualifications: The ideal candidate will have a strong quantitative background (time series analysis, regression models) and ability to code in python or MATLAB (though python will be used for most projects). All candidates must hold a PhD by the time of appointment. Preferred Qualifications: Previous experience in scalp EEG and/or fMRI strongly preferred, though related work in other electrophysiology methods will also be considered. A PhD in neuroscience, computer science, cognitive science, psychology, bioengineering, communication disorders, or other related fields is suggested. The Hamilton Lab is located in the Department of Speech, Language, and Hearing Sciences and is jointly affiliated with the Department of Neurology at Dell Medical School. The Huth Lab is located in the Departments of Neuroscience and Computer Science. The Hamilton and Huth labs are committed to fostering a supportive and diverse environment. We are strongly committed to mentoring our students and postdoctoral scholars to reach their goals. Our groups work as a multidisciplinary team, where each member’s contribution is valued. Our lab members come from a wide variety of fields including speech/language/hearing science, neuroscience, linguistics, music, physics, computer science, and psychology. The candidate is expected to work collaboratively with graduate students and research assistants in these fields. Apply at: https://utaustin.wd1.myworkdayjobs.com/UTstaff/job/UT-MAIN-CAMPUS/Postdocto…

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Professor position in Goettingen, Germany
by Rizzoli, Silvio Aug. 26, 2020

Aug. 26, 2020

Dear colleagues, I hope this email finds you well. My institute at the University Medical Center Goettingen, Germany, the Institute for Neuro- and Sensory Physiology, currently has an announcement for a W2 professorship position in the field of computational modeling of synaptic physiology. Our institute produces substantial quantitative data on synapses, from fluorescence imaging to biochemistry, mass spectrometry and electron microscopy (see for example Wilhelm et al., Science, 2014). We are looking for an investigator with substantial expertise in computational aspects, who would benefit from these data, and would be able to use them for important studies. This professorship will be integrated in an excellent neuroscience campus, and will benefit strongly from our collaborative research center CRC/SFB 1286, dedicated to Quantitative Synaptology (composed of more than 20 collaborating laboratories, from many excellent institutions). Our announcement can be found at: <https://jobs.zeit.de/jobs/universitaetsprofessur-w2-modellierung-synaptisch…>https://www.academics.com/jobs/university-professorship-w2-modeling-synapti… It would be great if you could also send this announcement to colleagues in your department, who may be interested in applying for this position. Best wishes, and thank you in advance, Silvio Rizzoli Prof. Dr. Silvio O. Rizzoli UNIVERSITÄTSMEDIZIN GÖTTINGEN GEORG-AUGUST-UNIVERSITÄT Direktor des Instituts für Neuro- und Sinnesphysiologie Zentrum Physiologie und Pathophysiologie Humboldtallee 23, 37073 Göttingen Telefon: 0551-39-5911 FAX: 0551-39–66031 E-Mail: srizzol(a)gwdg.de Sprecher des Centers Biostructural Imaging of Neurodegeneration (BIN) von-Siebold-Straße 3a, 37075 Göttingen Sprecher des Sonderforschungsbereichs 1286 Quantitative Synaptologie (Collaborative Research Center 1286 Quantitative Synaptology)

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Professorship in computational modeling of synaptic physiology at the University Medical Center Göttingen, Germany
by Erik De Schutter Aug. 26, 2020

Aug. 26, 2020

The University Medical Center Göttingen, Germany has announced a W2 professorship position in the field of computational modeling of synaptic physiology. The institute produces substantial quantitative data on synapses, from fluorescence imaging to biochemistry, mass spectrometry and electron microscopy. They are looking for an investigator with substantial expertise in computational aspects, who would benefit from these data, and would be able to use them for important studies. This professorship will be integrated in an excellent neuroscience campus, and will benefit strongly from our collaborative research center CRC/SFB 1286, dedicated to Quantitative Synaptology (composed of more than 20 collaborating laboratories, from many excellent institutions). The announcement can be found at: https://www.academics.com/jobs/university-professorship-w2-modeling-synapti…

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Postdoc/PhD/RA positions at ÖAW Acoustics Research Institute, Vienna
by Robert Baumgartner Aug. 19, 2020

Aug. 19, 2020

We are currently looking for enthusiastic researchers at all levels to join an exciting interdisciplinary research consortium addressing „Dynamic Auditory Predictions in Human and Non-human Primates (Dynamates)". It rests on a strong collaboration between cognitive neuroscience, cognitive biology, and computational modeling – for more information, visit our Dynamates website <https://www.kfs.oeaw.ac.at/dynamates>. The following positions are immediately available under my supervision at the Acoustics Research Institute of the Austrian Academy of Sciences: Postdoc <https://www.oeaw.ac.at/fileadmin/subsites/Jobs/ISF083PD220.pdf> focussing on computational models explaining the causal relationship between neural activity (EEG) and perception/behaviour in humans PhD Student <https://www.oeaw.ac.at/fileadmin/subsites/Jobs/ISF082DOC220.pdf> focussing on computational models for comparative behaviour Research Assistant <https://www.oeaw.ac.at/fileadmin/subsites/Jobs/ISF081STUD220.pdf> helping with (mainly EEG) data collection They are open until appropriate candidates are found. The 1st round of evaluation will start on Sept 1, 2020. Feel free to distribute! Best, Robert — Robert Baumgartner, PhD YIRG Leader | Research Associate Acoustics Research Institute Austrian Academy of Sciences Wohllebengasse 12-14, 1040 Vienna, Austria +43 1 51581-2527 Robert.Baumgartner(a)oeaw.ac.at https://www.kfs.oeaw.ac.at/baumgartner Like us on Facebook <https://www.facebook.com/SCHALLFORSCHUNG.OEAW/> Follow us on Twitter/oeaw <https://twitter.com/oeaw?lang=en> Visit us on Youtube <https://www.youtube.com/channel/UCY3rUdfN-VCjvfUWojWkayQ>

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Phd/Postdoc position for research on interpretable Deep Learning and brain modelling
by Wolfgang Maass Aug. 18, 2020

Aug. 18, 2020

We are looking for a highly talented and motivated Phd student or Postdoc to complement our team in the Faculty for Computer Science and Biomedical Engineering of Graz University of Technology in Austria. The researcher will work on advancing Deep Learning and methods for understanding its outcomes ("interpretable AI") for applications to large data-based cortical microcircuit models, using state-of-the-art supercomputing facilities. The goals are to elucidate the organization of computing and learning in neural networks of the brain, and to develop on this basis spike-based AI methods. The research will be based on recently developed algorithms and TensorFlow software for spiking neural networks, as published for example in G. Bellec, D. Salaj, A. Subramoney, R. Legenstein, and W. Maass. Long short-term memory and learning-to-learn in networks of spiking neurons. 32nd Conference on Neural Information Processing Systems (NIPS 2018), https://igi-web.tugraz.at/PDF/243.pdf G. Bellec, F. Scherr, A. Subramoney, E. Hajek, D. Salaj, R. Legenstein, and W. Maass. A solution to the learning dilemma for recurrent networks of spiking neurons. Nature Communications, 2020. .https://www.nature.com/articles/s41467-020-17236-y.pdf F. Scherr, C. Stoeckl, and W. Maass. One-shot learning with spiking neural networks. bioRxiv, 2020. https://igi-web.tugraz.at/PDF/256.pdf This is a fully funded research position in the Human Brain Project of the EU, which offers an exciting international interdisciplinary research environment. Requirements: --strong mathematical background and analytical skills --deep interest in understanding the function of neural networks in the brain --excellent programming skills --very good knowledge in Machine Learning Please send your CV, grades, motivation letter, and links to pdf of your master thesis and other relevant preceding work to charlotte.rumpf(a)tugraz.at -- Prof. Dr. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b , A-8010 Graz, Austria Tel.: ++43/316/873-5822 Fax ++43/316/873-5805 http://www.igi.tugraz.at/maass/Welcome.html

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Neurodata Without Borders (NWB) User Days Workshop - September 21-23
by Ryan Ly Aug. 17, 2020

Aug. 17, 2020

Neurodata Without Borders (NWB) is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build analysis tools for neurophysiology data. NWB is designed to store a variety of neurophysiology data, including data from intracellular and extracellular electrophysiology experiments, data from optical physiology experiments, behavioral data, and stimulus data. The NWB Team will be hosting the 9th NWB User Days Workshop remotely on September 21-23. The workshop schedule will be centered on Central European Time (UTC+2) and will focus primarily on user training, including lessons for complete beginners to NWB. Come learn how to get your data into the NWB data standard and use state-of-the-art data analysis, visualization, and management tools with NWB, e.g., Brainstorm, CaImAn, calciumImagingAnalysis, DANDI, DataJoint, MIES, NWB Explorer, NWB Widgets, SpikeInterface, and suite2p. Event page: https://neurodatawithoutborders.github.io/nwb_hackathons/HCK09_2020_Remote/ Register here: https://bit.ly/2PHbE34 (it's free) Learn more about NWB at our website: https://www.nwb.org/ Best, The NWB Team -- Ryan Ly Scientific Data Engineer Lawrence Berkeley National Laboratory 1 Cyclotron Road Mail Stop 59R4104 Berkeley, CA 94720 Email: rly(a)lbl.gov Pronouns: he/him

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Neural Data Analysis Online Course
by Maryam Aug. 17, 2020

Aug. 17, 2020

You are invited to “Neural Data Analysis Online Course” Dear Sir, Madam; ScienceBeam, which is a forefront technology provider of neuroscience applications, would like to take the opportunity to invite you for 10-session “Neural Data Analysis Online Course” that is going to start on September 7, 2020. During this course you will learn: ( Programming fundamentals: Variables, plots, loops ( How to compare ERPs in a statistical way: confidence intervals and bootstrapping ( EEG spectrum and spectrogram: from time to frequency and time-frequency ( More on spectrum: windowing and zero padding ( Analysis of coupled rhythms: covariance and coherence ( Filtering, filtering, and filtering! ( Cross-frequency coupling and Hilbert transform ( Brain states in sleep and Hidden Markov Model Hamed Yeganegi, PhD researcher in systems neuroscience, Technical University of Munich, Germany, is the instructor of this course. He is also a member of German Neuroscience Society (NWG) and Member of Federation of European Neuroscience Societies (FENS). Registration is open until September 4th. You won’t want to miss this! Don’t hesitate and register from the link below: Register NOW ! If you needed more information please contact us via Whatsapp or Mail: Whatsapp number: +86 133 8078 1282 Email: workshop(a)sciencebeam.com www.sciencebeam.com

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One Fellow position for closed-loop systems in neuroengineering @IIT Genova, ITALY
by Michela Chiappalone Aug. 17, 2020

Aug. 17, 2020

Dear Comp-Neuro community, A new opening for a 12-months fellowship position at the Pre-Doctoral level is available in our team, under the supervision of Dr Stefano Buccelli and myself at the Rehab Technologies Lab of the Istituto Italiano di Tecnologia (IIT), located in Genova at the IIT Center for Convergent Technologies. The fellow will carry out research on the development of a novel closed-loop architecture for applications in neuroengineering. More information on the position can be found below in this email. The application link can be found here: https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=en&job=2000002C The call expires on September 7th, 2020. Please forward this message to all the interested students. Thank you and best regards, Michela Chiappalone & Stefano Buccelli ---------------------------------------------------------------------------------------------------------------------------------------------------------------- One Fellow position for the development of a reference architecture for closed-loop systems for neuroengineering applications The Rehab Technologies INAIL-IIT lab, (http://rehab.iit.it/) at Istituto Italiano di Tecnologia (IIT), Genova, Italy, is seeking to appoint one Fellow at the pre-Doctoral level to carry out research on the development of novel closed-loop architecture for applications in neuroengineering. The Rehab Technologies Lab is an innovation lab aimed at developing new high tech prosthetic, orthotic and rehabilitation devices of high social impact and market potential. The Lab is primarily focused on disability and rehabilitation, and exploits a co-creation process which involves scientists, patients and therapists in all the phases of the design, realization and testing of devices developed within the lab. The Neuroengineering area of Rehab Technologies is focused on neural interfaces and neurorehabilitation. The team has a multidisciplinary expertise in engineering and neuroscience, with skills in in vitro/in vivo electrophysiology, signal processing of neural data (spikes, LFP, EEG), closed-loop systems, neurostimulation and innovative neuroprostheses. The primary research goals of the team consist of designing and testing novel 'personalized' neuroengineering solutions for brain repair and extracting functional biomarkers of recovery induced by the rehab-related training. In modern neuroscience, closed-loop systems delivering stimulation depending on to the actual brain state demonstrated to improve the efficacy of a therapy, also reducing the number of side effects. To build a closed-loop system, three steps are needed: reading, interpreting and writing the neural code. To 'read' the neural code, we need to record neural activity, by using either invasive or non-invasive techniques. 'Interpreting' or decoding the neural activity is obtained by means of (real-time) signal processing techniques. To 'write' the neural code, usually an electrical simulation approach is adopted (but other options are available). Nowadays, given the increased number of recording sites that can be acquired at the same time, there is a big demand for high-performance signal processing techniques in both clinical practice and basic research. Field-Programmable Gate Arrays (FPGA) are one of the most interesting options for the implementation of high-performance computations and are usually chosen as a first step towards the development of standalone devices. Learning how to implement an algorithm on FPGA can be prohibitive for non-experts and thus it is preventing many neuroscientists from realizing innovative closed-loop systems. Within this framework and to reduce the entry barrier in the development of closed-loop architectures on FPGA, this project will built up a rapid-prototyping, reference architecture for closed-loop neuroengineering applications by exploiting a model-based design approach (in Simulink). This will be reached by means of the following specific objectives: 1. Build a reference Simulink model to process neural data. 2. Take advantage of the HDL coder and the Fixed-Point Designer to implement the model on FPGA; 3. Establish use cases on commercially available systems (e.g. INTAN Stimulation/Recording system). The project will be carried out at the Rehab Technologies Lab of IIT, located in Genova at IIT Center for Convergent Technologies. To face this technological challenge, the Rehab Technologies Lab will share resources, competencies and motivation to achieve excellent results transferable to the neuroengineering field and, later, to clinics. We are looking for a highly motivated, outstanding candidate with the following profile: - A solid background in biomedical/electronics engineering - Strong programming skills, especially with the MathWorks products (Matlab, Simulink) - Master Degree in one of the above field (already obtained or to be obtained in the next two months) - Good communication skills and ability to cooperate - Proficiency in English Desirable skills: - Experience with Verilog/VHDL During this period, the selected candidate will develop the following skills and experience: - Principle of Neuroengineering and its applications - Model-based Design and Rapid Prototyping - Closed-loop architectures - Basic Electrophysiological skills - Interactions within a multidisciplinary Lab and for an International project To apply, please send your CV, title of the Master Thesis and (foreseen) date of graduation, cover letter and name and contacts of one/two referees using the form online. Deadline: September 7, 2020. Istituto Italiano di Tecnologia (IIT), with its headquarters in Genova, Italy, is a non-profit institution with the primary goal of creating and disseminating scientific knowledge and strengthening Italy's technological competitiveness. The institute offers state-of-the-art equipment and a top-level interdisciplinary research environment focused on robotics and computer vision, neuroscience, drug discovery, nanoscience and technology. Istituto Italiano di Tecnologia is an Equal Opportunity Employer that actively seeks diversity in the workforce. Please note that the data that you provide will be used exclusively for the purpose of professional profiles' evaluation and selection, and in order to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security. Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 - email: dpo[at]iit.it). ------------------------------------------------------------------------- Dr Michela Chiappalone, PhD Researcher Rehab Technologies IIT-INAIL Lab Phone : +39 010 71781743 E-mail : michela.chiappalone(a)iit.it<mailto:michela.chiappalone@iit.it> ISTITUTO ITALIANO DI TECNOLOGIA Via Morego 30, 16163 Genova Site: www.iit.it<http://www.iit.it>

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Web Conference /DMSE 2020, Denmark - Deadline Approaching[Third Batch Call for Submissions] .
by Fredrick Johnson Aug. 13, 2020

Aug. 13, 2020

International Conference on Data Mining and Software Engineering (DMSE 2020) September 26 ~ 27, 2020, Copenhagen, Denmark *WIKICFP Call* : http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=111118&copyownerid… *DBWORLD Call* : http://www.cs.wisc.edu/dbworld/messages/2020-08/1597292447.html Scope & Topics International Conference on Data Mining and Software Engineering (DMSE 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Data mining and Software Engineering. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on understanding Data mining and modern software engineering concepts and establishing new collaborations in these areas. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of data mining and software engineering. Topics of interest include, but are not limited to, the following • Advanced Topics in Software Engineering • Data Mining Applications • Computer Education • Data Mining in Modeling, Visualization, Personalization and Recommendation • Data Mining Systems and Platforms, Efficiency, Scalability and Privacy • Embedded System and Software • Foundations, Algorithms, Models, and Theory • Knowledge Processing • Knowledge-based Systems and Formal Methods • Languages and Formal Methods • Managing Software Projects • Mining Text, Semi-Structured, Spatio-Temporal, Streaming, Graph, Web, Multimedia • Multimedia and Visual Software Engineering • Quality Management • Search Engines and Information Retrieval • Software Engineering Decision Making • Software Engineering Practice • Software Maintenance and Testing • Software Process • Web Engineering • Web-based Education Systems and Learning Applications Accepted Papers List Learning for E-Learning-Aalen University, Germany. Magnetic Resonance Image Classification of Major Depression Disorder Based on Deep Learning-Beijing Technology and Business University, Beijing, China COSM: Controlled Over-sampling Method. A Methodological Proposal to Overcome the Class Imbalance Problem in Data Mining-CIRA (Italian Aerospace Research Centre),Italy A Process for Complete Autonomous Software Display Validation And Testing (Using A Car-cluster)-SAP Labs India Pvt Lmt.,India Analysis of the Displacement of Terrestrial Mobile Robots in Corridors Using Paraconsistent Annotated Evidential Logic Et-Bialystok University of Technology,Poland A Study on the Minimum Requirements for the On-line, Efficient and Robust Validation of Neutron Detector Operation and Monitoring of Neutron Noise Signals using Harmony Theory Networks-University of Piraeus, France Penalized Bootstrapping for Reinforcement Learning in Robot Control-University of Bonn,Germany Deep Reinforcement Learning for Navigation in Cluttered Environments-University of Bonn, Germany New Hybrid Artificial Intelligent Models Basedon Optimized-support Vector Machine and Locallylinear Neuro fuzzy for the Supplier Assessment Problem-Islamic Azad University, Iran IoT Learning Model for Smart Universities: Architecture, Challenges, and Applications-Whitecliffe College of Technology & Innovation, New Zealand The Principles of the Law General on the Protection of Personal Data and their Importance-Paulista University, Brazil. Controlled Machine Text Generation of Football Articles-University of Warsaw, Poland On the Comparison of Deep Neural Networks for Document Retrieval-Institute for Community Medicine, Germany Evaluationn of Company Investment value based on Machine Learning-Beijing University of Technology, China Performance evaluation of Precoded Band Codes and Hamming Norm Decoders in Random Linear Network Coding-National Engineering School of Tunis, Tunisia Neurological Signals Compression and Encryption for Security Transmission Based on IOMT: A Tele-neurological Diagnosis-University of Anbar, Iraq. Paper Submission Authors are invited to submit papers through the conference Submission System . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed). Here’s where you can reach us : dmse(a)dmse2020.org or dmsesecretary(a)gmail.com Submit your work Today! Regards, Fredrick.

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