- Comp-neuro - lists.cnsorg.org

Computational neuroscience - PhD/Postdoc - Cheng Lab, Bochum

by Vinita Samarasinghe

We (Cheng Lab <https://www.ini.rub.de/research/groups/computational_neuroscience/>, Ruhr University Bochum <https://rub.de/>, Germany) are looking to fill two positions in the area of computational neuroscience each for 3 years. _*Positions*_ 1. Postdoc: Join the team on project F01 <https://sfb1280.ruhr-uni-bochum.de/en/research/projects/f01/> of the Collaborative Research Center “Extinction Learning” SFB 1280 <https://sfb1280.ruhr-uni-bochum.de/en/home/> to: * analyze learning dynamics in behavioral, neural, and psychophysiological data, which will be collected by other projects within the SFB 1280. * compare the learning dynamics between individuals, species, learning phases and learning paradigms, * develop algorithms to analyze the learning dynamics, * develop and study computational models of learning dynamics, and * coordinate research with other participating projects. 2. PhD student or Postdoc: Develop and study computational models of episodic memory and spatial navigation by: * extending models based on large networks of biologically plausible spiking neurons with synaptic plasticity, * studying the generation and learning of complex spatial behaviors in the model, * quantitatively comparing the model output to the spatial behavior of mammals, and * studying the role of episodic memory in spatial navigation. The research groupis highly dynamic and uses diverse computationalmodeling approachesincludingbiological neural networks, cognitive modeling, and machine learning to investigatelearning and memory in humans and animals. _*Qualifications*_ * Adoctorate degreein neuroscience, physics, mathematics, electrical/biomedical engineering or a closely related field. In exceptional cases, graduate students with a Masters degree in these fields, but nodoctorate degree, may be considered. * Relevant experience in mathematical modeling together with a solid mathematics background * Relevant research experience in neuroscience or a related field (only position 1) * Be able to think algorithmically and have excellent programming skills (e.g., Python) * Excellent communication skills in English * Work well in a team. The Ruhr University Bochum is home to a vibrant research community in neuroscienceand cognitive science. The Institute for Neural Computation <https://www.ini.rub.de/> in the Faculty of Computer Science <https://informatik.rub.de/en/> combines different areas of expertise ranging from experimental and theoretical neuroscienceto machine learning androbotics. Please send your application, including CV, transcripts (bachelor & master) and research statement electronically, as a *single PDF* file, to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de>. In addition, at least two academic references mustbe sent independently to the above email address. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. We are committed to providing a supportive work environment for female researchers, in particular those with young children. Our university provides mentoring and coaching opportunities specifically aimed at women in research. We have a strong research network with female role models and will provide opportunities to networkwith them. Wherever possible, events will be scheduled during regular childcare hours. Special childcare will be arranged if events have to be scheduled outside of regular hours, in case of sickness and during school or daycare closures. Where childcare is not an option parents will be offered a home office solution. Contact person: Vinita Samarasinghe, samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de> -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/73 Postfachnummer 110 Universitätstr. 150 44801 Bochum Tel: +49 (0) 234 32 27996 Email:samarasinghe@ini.rub.de

Sept. 12, 2022

PhD position in Neurotechnology at the Friedrich-Alexander-University (FAU) Erlangen-Nuremberg, Germany

by Reichenbach, Tobias

The Chair for Sensory Neuroengineering at the new Department Artificial Intelligence in Biomedical Engineering is looking for a PhD student to work on an innovative project in neurotechnology. Together with partners in the Cluster4Future SEMECO (TU Dresden, MED-EL, Fraunhofer) you will develop a Brain-Computer-Interface (BCI) for the next generation of hearing aids. To this end you will develop AI methods for analyzing brain signals and for steering the processing of acoustic signals. The prototype hearing aids with neurofeedback should be then be able to abadjust to the needs of their users and to adapt in real time. AI at the interface to neurobiology is a highly timely topic of immense societal relevance. We offer you the possibility to actively shape this exciting and rapidly developing field. We support your work through: - A lively scientific environment within the Department and the possibility to cooperate with excellent partners at the Friedrich-Alexander-University Erlangen-Nürnberg, at Imperial College London as well as with industry partners - An excellent environment to conduct leading science and to realise own scientific ideas - An excellent training in the development of AI methods for neuronal data - Development of your personal strengths, for instance through extensive courses on personal development - 26 days of holiday per year The renumeration is according to Group 13 of the German public service (TV-L). FAU is the most innovative university in Germany and ranks second among the most innovative European universities. It is located in one of the most attractive regions in Germany. Erlangen is a bicycle-friendly city with 100,000 inhabitants, former home of the Huguenots as well as a key location for industry. It is close to Nuremberg, a city with a population of half a million and a metropolitan flair. The mixture of academia, innovative companies, art and culture makes the region the perfect place for creative minds, keen athletes and nature lovers. To apply, please send a letter detailing your motivation, a CV, copies of your degrees and details of two referees. Please combine all documents into a single pdf and send them per email with subject “Application PhD student” to Prof. Dr. Tobias Reichenbach (tobias.j.reichenbach(at)fau.de<http://fau.de>). More information is available here: https://www.jobs.fau.de/jobs/phd-student-in-neurotechnology-u98170569/ ------------------------------------------- Prof. Dr. Tobias Reichenbach Chair of Sensory Neurotechnology Department Artificial Intelligence in Biomedical Engineering (AIBE) Friedrich-Alexander-University (FAU) Erlangen-Nürnberg Werner-von-Siemens-Strasse 61 91052 Erlangen https://www.neurotech.tf.fau.eu/

Sept. 10, 2022

Python Package: Echo State Networks

by Fabrizio Damicelli

Dear Computational Neuroscience Community, I would like to point you to a potentially useful Python Package that might be of interest for your research, especially in the realms of "Biologically-inspired Neural Networks", "Shallow Learning" and "Recurrent Neural Networks" in general. "echoes": Machine Learning with Echo State Networks, a scikit-learn compatible package. Code Repository: https://github.com/fabridamicelli/echoes A few interesting features: - scikit-learn compatible, i.e. scikit-learn tools such as GridSearchCV should work out-of-the-box - It is light-weight and fast (`numba` accelerated), i.e. many experiments can be simply run on a laptop - Flexible and customizable, e.g. use arbitrary connectivity, add custom activations, visualize neurons activity, etc. - Installation and getting started is easy: `pip install echoes` - Example notebooks: https://github.com/fabridamicelli/echoes/tree/master/examples/notebooks - Documentation: https://fabridamicelli.github.io/echoes/ As of today, a few people already trust it and the package registers >18K total downloads, ~500/month (pypi.org<http://pypi.org/>) and has been used already in a few research projects: - Hadaeghi et. al. (2021) Spatio-temporal feature learning with reservoir computing for T-cell segmentation in live-cell Ca2+ fluorescence microscopy: www.nature.com/articles/s41598-021-87607-y#Sec4<http://www.nature.com/articles/s41598-021-87607-y#Sec4> - Damicelli et.al<http://et.al/>. (2021) Brain Connectivity meets Reservoir Computing: www.biorxiv.org/content/10.1101/2021.01.22.427750v1.abstract<http://www.biorxiv.org/content/10.1101/2021.01.22.427750v1.abstract> - Fakhar et. al. (2022) Causal Influences Decouple From Their Underlying Network Structure In Echo State Networks: arxiv.org/abs/2205.11947<http://arxiv.org/abs/2205.11947> Check it out and any feedback/suggestions/bug reports are more than welcome (simply open an issue: https://github.com/fabridamicelli/echoes/issues) All the best, Fabrizio

Sept. 9, 2022

Postdoc / Junior Scientist / Research fellow positions in Complex Networks, Prague, Czech Republic

by Magda Pokorna

The following positions are open in the department of Complex Systems at the Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic. Applications for all positions will be reviewed on a rolling basis*with a first cut-off point on *30. **9**. 2022.** 1. *Postdoctoral / Junior Scientist position in Multimodal Neuroimaging Machine Learning, Prague, Czech Republic* A Postdoc or Junior Scientistposition is available to join the _Complex Networks and Brain Dynamics group <http://cobra.cs.cas.cz/>_for the project: /*“Predicting functional outcome in schizophrenia from multimodal neuroimaging and clinical data“*/funded by the Czech Health Research Council.The project involves the development of tools to predict the functional outcome of schizophrenia from multimodal neuroimaging, clinical and cognitive measurements taken early after disease onset. To overcome limitations due to high dimensionality of data, we combine robust machine-learning tools, data-driven feature selection and theory-based brain network priors. The project is carried out in collaboration with the National Institute of Mental Health, using its unique large rich imaging, cognitive and biochemical data of early stage schizophrenia patients. *For more information, conditions and application* see https://www.cs.cas.cz/job-offer/postdoctoral-junior-scientist-position-Hlin…. 2. *Researc**h Fellow / Postdoc positions in Complex Networks and Brain Dynamics, Prague, Czech Republic* We are looking for new team members to join the _Complex Networks and Brain Dynamics group <http://cobra.cs.cas.cz/>_to work on its interdisciplinary projects. The group is part of the Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences - based in Prague, Czech Republic, _https://www.cs.cas.cz/ <https://www.cs.cas.cz/>_.We focus on the development and application of methods of analysis and modelling of real-world complex networked systems, with particular interest in the structure and dynamics of human brain function. Our main research areas are neuroimaging data analysis (fMRI & EEG, iEEG, anatomical and diffusion MRI), brain dynamics modelling, causality and information flow inference, nonlinearity and nonstationarity, graph theory, machine learning and multivariate statistics; with applications in neuroscience, climate research, economics and general communication networks. *More information about the group at *_*http://cobra.cs.cas.cz/* <http://cobra.cs.cas.cz/>_*. **For more information, conditions and application* see https://www.cs.cas.cz/job-offer/research-fellow-postdoc-position-Hlinka1-20…. *Do not hesitate to contact the **group leader**/ Principal Investigator for informal inquiries: Ing. Mgr. Jaroslav Hlinka, Ph.D. *_*hlinka[at]cs.cas.cz* <mailto:hlinka@cs.cas.cz>_*, *_*http://www.cs.cas.cz/hlinka/*_

Sept. 9, 2022

Postdoctoral Position at UConn in Systems and Computational Neuroscience

by Ian Stevenson

The Physiological Acoustics Lab (http://escabilab.uconn.edu) at the University of Connecticut seeks applicants for a postdoctoral position in systems and computational neuroscience. We are seeking highly motivated and creative applicants that can lead a project on perception and neural coding of speech and vocalizations in the presence of competing natural environmental noises (e.g., restaurant noise, busy street, construction noise etc.). The broad project goal is to study the neural basis for listening in noisy environments and to devise a general computational theory that accounts for perception and physiology. The project will use a variety of experimental approaches including human perception, awake animal electrophysiology, large scale neural recording, and computational modeling. UConn has a vibrant neuroscience community and there are opportunities for collaboration between departments and institutes. The primary appointment is in Biomedical Engineering, but the work will be conducted in collaboration with the Behavioral Neuroscience division in the Psychology department (Statistical Neuroscience Lab, http://stevenson.lab.uconn.edu; Sensory Perception and Neuroscience Lab, http://read.lab.uconn.edu) as well as Electrical and Computer Engineering and Biomedical Engineering. Qualifications: A PhD in Neuroscience, Biomedical Engineering, Electrical Engineering, Computational Neuroscience, or a related field is required. The ideal candidate will have an interdisciplinary research background in computational and systems neuroscience with prior research experience in awake animal neurophysiology. A strong analytic background in neural data analysis is desirable, particularly modeling neural systems and analyzing datasets from large-scale multi-channel neural recordings. Experience with acoustic signal processing, sound recognition, and machine learning is also desirable. Appointment: The position is funded through an R01 grant and salaries follow NIH post-doctoral scale and are based on experience. Applicants should email escabi(a)engr.uconn.edu a single PDF file containing: 1) resume including past research experience and published work 2) one page statement of prior research experience 3) one page statement of future research interests and objectives 4) names of at least two individuals who can provide reference letters Ian Stevenson Associate Professor University of Connecticut Department of Psychological Sciences stevenson.lab.uconn.edu

Sept. 8, 2022

Job: ML Engineer to extend ReservoirPy library for health data (Reservoir Computing)

by Xavier Hinaut

We are looking for an engineer for at least one year to work with the open source ReservoirPy library on health data. You will be working in Bordeaux, France in the Mnemosyne computational neuroscience group https://team.inria.fr/mnemosyne <https://team.inria.fr/mnemosyne> in collaboration with other Bordeaux teams involved in biostatistics and machine learning. More info and online application: https://jobs.inria.fr/public/classic/en/offres <https://jobs.inria.fr/public/classic/en/offres> * ReservoirPy ReservoirPy [1, 2, 3] is a simple user-friendly library based on Python scientific modules. It provides a flexible interface to implement efficient Reservoir Computing (RC) [5] architectures with a particular focus on Echo State Networks (ESN) [4]. Advanced features of ReservoirPy allow to improve computation time efficiency on a simple laptop compared to basic Python implementation. Some of its features are: offline and online training, parallel implementation, sparse matrix computation, fast spectral initialization, advanced learning rules (e.g. Intrinsic Plasticity) etc. It also makes possible to easily create complex architectures with multiple reservoirs (e.g. deep reservoirs), readouts, and complex feedback loops. Moreover, graphical tools are included to easily explore hyperparameters with the help of the hyperopt library. It includes several tutorials exploring exotic architectures and examples of scientific papers reproduction. Github: https://github.com/reservoirpy/reservoirpy <https://github.com/reservoirpy/reservoirpy> Documentation: https://reservoirpy.readthedocs.io <https://reservoirpy.readthedocs.io/> Related projects: https://github.com/reservoirpy <https://github.com/reservoirpy> Twitter: https://twitter.com/reservoirpy <https://twitter.com/reservoirpy> * Deadline: 20th of September 2022 For informal questions send an email to xavier dot hinaut at inria dot fr. Online application: https://jobs.inria.fr/public/classic/en/offres <https://jobs.inria.fr/public/classic/en/offres> * Contract Engineer contract of 1 year, with possibility to extend the contract to more years or to continue in the team as PhD student. * Benefits package - Subsidized meals - Partial reimbursement of public transport costs - Possibility of partial teleworking and flexible organization of working hours - Professional equipment available (videoconferencing, loan of computer equipment, etc.) - Social, cultural and sports events and activities - Access to vocational training - Social security coverage [1] Trouvain N, Pedrelli L, Dinh TT, Hinaut X (2020). Reservoirpy: an efficient and user-friendly library to design echo state networks. International Conference on Artificial Neural Networks, 494-505. https://hal.inria.fr/hal-02595026v2/document <https://hal.inria.fr/hal-02595026v2/document> [2] Trouvain, N., Rougier, N. P., & Hinaut, X. (2022). Create Efficient and Complex Reservoir Computing Architectures with ReservoirPy. In FROM ANIMALS TO ANIMATS 16: The 16th International Conference on the Simulation of Adaptive Behavior (SAB2022). https://hal.inria.fr/hal-03761440/document <https://hal.inria.fr/hal-03761440/document> [3] Nathan Trouvain, Xavier Hinaut. reservoirpy: A Simple and Flexible Reservoir Computing Tool in Python. 2022. HAL preprint hal-03699931. https://hal.inria.fr/hal-03699931/document <https://hal.inria.fr/hal-03699931/document> [4] Jaeger, H., & Haas, H. (2004). Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication. science, 304(5667), 78-80. [5] Lukoševičius, M., & Jaeger, H. (2009). Reservoir computing approaches to recurrent neural network training. Computer Science Review, 3(3), 127-149. Xavier Hinaut Inria Research Scientist www.xavierhinaut.com -- +33 5 33 51 48 01 Mnemosyne team, Inria, Bordeaux, France -- https://team.inria.fr/mnemosyne & LaBRI, Bordeaux University -- https://www4.labri.fr/en/formal-methods-and-models & IMN (Neurodegeneratives Diseases Institute) -- http://www.imn-bordeaux.org/en --- Our Reservoir Computing library: https://github.com/reservoirpy/reservoirpy

Sept. 6, 2022

Multiple Vacancies at the University for Melbourne

by Uwe Aickelin

Hi, Hope this message finds you well. Please consider sharing this with any interested researchers. The University of Melbourne’s School of Computing and Information Systems is recruiting for 4x open positions. Application deadlines: Sep 26, 2022 (Australian Eastern Daylight Time) Lecturer/Senior Lecturer in machine learning: https://go.unimelb.edu.au/282e Lecturer/Senior Lecturer in theory of computing: https://go.unimelb.edu.au/f82e Lecturer/Senior Lecturer in information systems: https://go.unimelb.edu.au/482e Senior Lecturer/Associate Professor in fairness: https://go.unimelb.edu.au/h82e (These are continuing positions equiv. US tenure track research & teaching / faculty positions at a range of levels.) We’re excited to invite applications from individuals passionate about research, training, teaching, and engagement, to join us at Australia’s premier university, situated in one of the world’s most liveable cities. Best, Uwe Aickelin -- Professor Uwe Aickelin | Head of School of Computing and Information Systems Faculty of Engineering and Information Technology Level 3, Melbourne Connect – 700 Swanston Street The University of Melbourne, Victoria 3010 Australia T: +61 3 8344 3635 E: uwe.aickelin(a)unimelb.edu.au<mailto:uwe.aickelin@unimelb.edu.au> http://aickelin.com/ | http://linkedin.com/in/aickelin

Sept. 6, 2022

Neo community review extended to Sep 29 - call for comments and feedback

by Malin Sandström

Dear all, INCF is asking for your help to review the Neo object model <https://www.incf.org/sbp/neo>for electrophysiology data, to assess its value as a community standard. Participating is simple; read the INCF SBP committee review report <https://f1000research.com/documents/11-658> on F1000 and leave your feedback in the comments! You can comment to express your support, to point out possibilities for improvement - or both. We are especially interested in hearing from Neo users and from tool developers who have implemented support for Neo or use Neo as part of their workflow. Please give us your feedback in a comment as soon as possible, but latest September 29: f1000research.com/documents/11-658 More information: Neo <https://www.incf.org/sbp/neo> is an object model for handling electrophysiology data in multiple formats. It is suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. Neo has been implemented as a Python package for working with electrophysiology data, together with support for reading a wide range of neurophysiology file formats (including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, Igor Pro), and support for writing to a subset of these formats plus non-proprietary formats including Kwik and HDF5. Read more about Neo: Project page <https://neuralensemble.org/neo/> Documentation <https://neo.readthedocs.io/en/stable/> Github <https://github.com/NeuralEnsemble/python-neo> Paper <https://www.frontiersin.org/articles/10.3389/fninf.2014.00010/full> -- Malin Sandström, PhD Community Engagement Officer malin.sandstrom(a)incf.org ORCID: 0000-0002-8464-2494 International Neuroinformatics Coordinating Facility Karolinska Institutet Nobels väg 15 A SE-171 77 Stockholm Sweden http://www.incf.org

Sept. 6, 2022

3rd SMILES workshop in less than one week! (12 sept.)

by Xavier Hinaut

The 3rd SMILES (Sensorimotor Interaction, Language and Embodiment of Symbols) Workshop will take place both on site and virtually at ICDL 2022 conference. **9am-6pm UTC+1 (London time) on September 12, 2022** * Invited talks: - Joanna Raczaszek-Leonardi (University of Warsaw, Poland) - Joel Z Leibo (DeepMind, London, UK) - Lorijn Zaadnoordijk (Trinity College Dublin, Ireland) - Martin Butz & Christian Gumbsch (University of Tübingen, Germany) - Ida Momennejad (Microsoft Research NYC, USA) * Important info: - Registration: https://forms.gle/No8xFFkmfKXXdNMm7 (if you come onsite, you also need to register here: https://icdl2022.qmul.ac.uk/?page_id=50 ) - Workshop website: https://sites.google.com/view/smiles-workshop/ - Onsite venue: Graduate Center, Queen Mary University of London, UK. More info here: https://icdl2022.qmul.ac.uk/?page_id=103 - Venue online: via Zoom and Discord group. - Join our Discord: https://discord.gg/sBZbdSWRvJ (expires after 100 hits) - Follow us on Twitter: https://twitter.com/SMILESconf * 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, - Symbol grounding and symbol emergence, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and language 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 - organizers: Xavier Hinaut, Clément Moulin-Frier, Silvia Pagliarini, Joni Zhong, Michael Spranger, Tadahiro Taniguchi, Anne Warlaumont. - ICDL conference website: https://icdl2022.qmul.ac.uk/ Xavier Hinaut on behalf of the SMILES workshop organisers: - Clément Moulin-Frier, Inria and Ensta ParisTech, Bordeaux, France - Anne Warlaumont, UCLA, Los Angeles, USA - Silvia Pagliarini, UCLA, Los Angeles, USA - Michael Spranger, Sony AI and Sony CSL, Tokyo, Japan - Tadahiro Taniguchi, Ritsumeikan University, Kyoto, Japan - Junpei Zhong, Hong Kong Polytechnic University, Hong Kong, China Xavier Hinaut Inria Research Scientist www.xavierhinaut.com <http://www.xavierhinaut.com/> -- +33 5 33 51 48 01 Mnemosyne team, Inria, Bordeaux, France -- https://team.inria.fr/mnemosyne <https://team.inria.fr/mnemosyne> & LaBRI, Bordeaux University -- https://www4.labri.fr/en/formal-methods-and-models <https://www4.labri.fr/en/formal-methods-and-models> & IMN (Neurodegeneratives Diseases Institute) -- http://www.imn-bordeaux.org/en <http://www.imn-bordeaux.org/en> --- Our new release of Reservoir Computing library: https://github.com/reservoirpy/reservoirpy <https://github.com/reservoirpy/reservoirpy>

Sept. 5, 2022

2 year independent Postdoc position in human centered AI (German required)

by Laurenz Wiskott

The Institute for Neural Computation of the Faculty of Computer Science is looking for a Postdoc (m,f,x) for 2 years, full-time, TVL E13 The Institute for Neural Computation is part of the Faculty of Computer Science at the Ruhr-University Bochum, see https://www.ini.rub.de/. It focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. There is an open position for a postdoc in the group of Prof. Dr. Laurenz Wiskott to be filled October 1st. The project is part of the competence center HUMAINE for human-centered artificial intelligence, see https://humaine.info/, and will be developed in close collaboration with colleagues at RUB and application partners in industry, among others. We offer: * An interesting interdisciplinary environment in the field of Artificial Intelligence / Machine Learning. * Opportunity to develop an independent research profile and your own research group. * Opportunity to pursue further scientific qualification. * Diverse and interesting contacts at the university, in transfer, and in industry. * A lot of room for own ideas and initiatives. Your opportunities: * Acquiring and maintaining industry contacts. * Scientific advice for companies to help them introduce AI in work processes. * Advising corresponding PhD and student projects. * Coordination of events and teaching of advanced training courses about human-centered AI for developers and decision makers in industry Your profile: * Very good PhD in mathematics, computer science, engineering, or a related field * Solid knowledge in Artificial Intelligence / Machine Learning. * Good programming and mathematical skills * Good command of German. * Good organizational and communicative abilities. * Advantageous: + Experience in industry cooperations and interdisciplinary projects. + Programming skills in Python. Our offerings: * Challenging and varied tasks with a high degree of personal responsibility * Support from and cooperation with competent colleagues * A dynamic environment * Fair and flexible working hours * Support in reconciling family and work/academics (including childcare placement, holiday offers, mobile children's room) Additional information: The load of teaching will be calculated according to § 3 of Lehrverpflichtungsverordnung (state of North Rhine-Westphalia). Contact details for your application: Prof. Dr. Laurenz Wiskott, Phone: +49 234 32 27997 Travel expenses for interviews cannot be refunded. For information on the collection of personal data in the application process see: https://www.ruhr-uni-bochum.de/en/information-collection-personal-data-appl…. We are looking forward to receiving your application with the specification ANR: 800 until 30.09.2022, send by e-mail to the following address: laurenz.wiskott(a)rub.de extent: full-time duration: temporary beginning: as soon as possible application deadline: 30.09.2022 The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is RUB’s declared aim. The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome.

Sept. 5, 2022