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- 29 participants
- 7414 messages
Job Opening: Professor / Associate Professor / Assistant Professor (Computer Science) at Hong Kong Baptist University
by COMP HKBU
The Department of Computer Science at Hong Kong Baptist University,
presently offers BSc, MSc, MPhil, and PhD programmes, is now seeking
outstanding applicants for the following faculty positions on tenure-track.
*Professor / Associate Professor / Assistant Professor (Computer Science)
(PR0311/18-19) *
The appointees will perform high-impact research; to teach and manage
programmes at undergraduate and postgraduate levels, as well as to
contribute to professional and institutional services. Collaboration with
other faculty members in research and teaching is also expected. They will
be encouraged to collaborate with colleagues within the Department to
contribute to two special thematic applications including (a) health
informatics and (b) secure and privacy-aware computing, and/or outside the
Department to contribute to interdisciplinary research projects under our
University’s Research Cluster on Data Analytics and A.I. in X.
Applicants should possess a PhD degree in Computer Science, Computer
Engineering, Information Systems, or a related field, and sufficiently
demonstrate abilities to conduct high-quality research in one of the
Department’s key research areas: (i) computational intelligence, (ii)
databases and information management, (iii) networking and systems, and
(iv) pattern recognition and machine learning. Applicants should also show
strong commitment to undergraduate and postgraduate teaching in computer
science and/or information systems, possess track record of innovative
research and high-impact publications, and be able to bid for and pursue
externally-funded research programmes. Special consideration will be given
to candidates with research background related to financial technologies,
and secure and privacy-aware computing.
Initial appointment will be made on a fixed-term contract of three years.
Re-appointment thereafter will be subject to mutual agreement.
For enquiry, please contact Dr. William Cheung, Head of Department (email:
william(a)comp.hkbu.edu.hk) More information about the Department can be
found at http://www.comp.hkbu.edu.hk.
Those who have responded to the advertisement posted in March 2019 need not
re-apply.
*Rank and salary will be commensurate with qualifications and experience.*
*Application Procedure*:
Applicants are invited to submit their applications at the HKBU
e-Recruitment System (jobs.hkbu.edu.hk) with samples of publications,
preferably three best ones out of their most recent publications/works.
Applicants should also request two referees to send in confidential letters
of reference, with PR number (stated above) quoted on the letters, to the
Personnel Office (Email: recruit(a)hkbu.edu.hk) direct. Those who are not
invited for interview 4 months after the closing date may consider their
applications unsuccessful. All application materials including publication
samples, scholarly/creative works will be disposed of after completion of
the recruitment exercise. Details of the University’s Personal Information
Collection Statement can be found at http://pers.hkbu.edu.hk/pics.
The University reserves the right not to make an appointment for the posts
advertised, and the appointment will be made according to the terms and
conditions applicable at the time of offer.
Closing Date: *25 January 2020 (or until the positions are filled)*
URL: https://www.comp.hkbu.edu.hk/v1/?page=job_vacancies&id=503
Jan. 2, 2020
PhD AND POSTDOC POSITIONS IN COMPUTATIONAL NEUROSCIENCE IN BASEL, SWITZERLAND
by Rava A. da Silveira
*Several DOCTORAL and POSTDOCTORAL openings in the lab of RAVA AZEREDO DA
SILVEIRA at the IOB, University of Basel*
We invite applications for several Ph.D. and postdoctoral positions at the
IOB, University of Basel, in Switzerland. Research questions will be chosen
from a broad range of topics in theoretical/computational neuroscience and
cognitive science (see the description of the lab’s activity, below).
Candidates with backgrounds in mathematics, statistics, artificial
intelligence, physics, computer science, engineering, biology, and
psychology are welcome. Experience with data analysis and proficiency with
numerical methods, in addition to familiarity with neuroscience topics and
mathematical and statistical methods, are desirable. Equally desirable are
a spirit of intellectual adventure, eagerness, and drive.
Doctoral and postdoctoral salaries will be highly competitive.
*Deadline*
For full consideration, please apply by 30 January 2020.
*How to apply*
Please send a letter of motivation, a statement of research interests
limited to two pages, a curriculum vitae including a list of publications,
and any relevant publications to rava(a)iob.ch, and arrange for three letters
of recommendations to be sent to the same address. In all email
correspondence, please include the mention “APPLICATION-BASEL-PHD” or
“APPLICATION-BASEL-POSTDOC” in the subject header, otherwise the
application will not be considered.
*Description of the lab’s activity*
Rava Azeredo da Silveira’s lab focuses on a range of topics in theoretical
and computational neuroscience and cognitive science. These topics,
however, are tied together through a central question: How does the brain
represent and manipulate information?
Among the more concrete approaches to this question, the lab analyses and
models neural activity in circuits that can be identified, recorded from,
and perturbed experimentally, such as visual neural circuits in the retina
and the cortex. Establishing links between physiological specificity and
the structure of neural activity yields an understanding of circuits as
building blocks of cerebral information processing. On a more abstract
level, the lab investigates the representation of information in
populations of neurons, from a statistical and algorithmic -- rather than
mechanistic -- point of view, through theories of coding and data analyses.
These studies aim at understanding the statistical nature of
high-dimensional neural activity in different conditions, and how this
serves to encode and process information from the sensory world.
In the context of cognitive studies, the lab investigates mental processes
such as inference, learning, and decision-making, through both theoretical
developments and behavioral experiments. A particular focus is the study of
neural constraints and limitations and, further, their impact on mental
processes. Neural limitations impinge on the structure and variability of
mental representations, which in turn inform the cognitive algorithms that
produce behavior. The lab explores the nature of neural limitations, mental
representations, and cognitive algorithms, and their interrelations.
Dec. 29, 2019
PhD AND POSTDOC POSITIONS IN COMPUTATIONAL NEUROSCIENCE AT ENS, PARIS
by Rava A. da Silveira
*Several DOCTORAL and POSTDOCTORAL openings in the lab of RAVA AZEREDO DA
SILVEIRA at the Ecole Normale Supérieure, Paris*
We invite applications for several Ph.D. and postdoctoral positions at the
Ecole Normale Supérieure, in Paris. Research questions will be chosen from
a broad range of topics in theoretical/computational neuroscience and
cognitive science (see the description of the lab’s activity, below).
Candidates with backgrounds in mathematics, statistics, artificial
intelligence, physics, computer science, engineering, biology, and
psychology are welcome. Experience with data analysis and proficiency with
numerical methods, in addition to familiarity with neuroscience topics and
mathematical and statistical methods, are desirable. Equally desirable are
a spirit of intellectual adventure, eagerness, and drive.
Doctoral and postdoctoral salaries will be competitive, appreciably higher
than standard French salaries.
The ENS, together with a number of neighboring institutions (College de
France, Institut Curie, ESPCI, Sorbonne Université, and Institut Pasteur),
offers a rich scientific and intellectual environment, with a strong
representation in computational neuroscience and related fields.
*Deadline:*
For full consideration, please apply by 30 January 2020.
*How to apply:*
Please send a letter of motivation, a statement of research interests
limited to two pages, a curriculum vitae including a list of publications,
and any relevant publications to rava(a)ens.fr, and arrange for three letters
of recommendations to be sent to the same address. In all email
correspondence, please include the mention “APPLICATION-PARIS-PHD” or
“APPLICATION-PARIS-POSTDOC” in the subject header, otherwise the
application will not be considered.
*Description of the lab’s activity:*
Rava Azeredo da Silveira’s lab focuses on a range of topics in theoretical
and computational neuroscience and cognitive science. These topics,
however, are tied together through a central question: How does the brain
represent and manipulate information?
Among the more concrete approaches to this question, the lab analyses and
models neural activity in circuits that can be identified, recorded from,
and perturbed experimentally, such as visual neural circuits in the retina
and the cortex. Establishing links between physiological specificity and
the structure of neural activity yields an understanding of circuits as
building blocks of cerebral information processing. On a more abstract
level, the lab investigates the representation of information in
populations of neurons, from a statistical and algorithmic -- rather than
mechanistic -- point of view, through theories of coding and data analyses.
These studies aim at understanding the statistical nature of
high-dimensional neural activity in different conditions, and how this
serves to encode and process information from the sensory world.
In the context of cognitive studies, the lab investigates mental processes
such as inference, learning, and decision-making, through both theoretical
developments and behavioral experiments. A particular focus is the study of
neural constraints and limitations and, further, their impact on mental
processes. Neural limitations impinge on the structure and variability of
mental representations, which in turn inform the cognitive algorithms that
produce behavior. The lab explores the nature of neural limitations, mental
representations, and cognitive algorithms, and their interrelations.
Dec. 29, 2019
Postdoctoral Positions in Theoretical Neuroscience @ Higher School of Economics, Moscow Russia
by boris gutkin
Post-doctoral position in Theoretical Neuroscience
DEADLINE 9 February
More Information: https://iri.hse.ru/cognitive_neuroscience3 <https://iri.hse.ru/cognitive_neuroscience3>
Application link: https://iri.hse.ru/polls/323647081.html
The Higher School of Economics Centre for Cognition & Decision Making <https://www.hse.ru/en/cdm-centre/> of the Institute of Cognitive Neuroscience in Moscow, Russia, invites applications for postdoctoral research positions in computational and mathematical approaches to understanding neural function and cognition at Theoretical Neuroscience Group (TNG).
Research interests of the TNG at the Centre for Cognition and Decision Making are wide ranging, carried out in collaboration with the experimental labs at the Center. Current research topics include computational psychiatry, computational neuroeconomics, information processing in neurons and circuits, as well as role of oscillations in cognition. The candidate will have the opportunity to further define and expand the Group’s research programme.
We are seeking highly qualified and motivated candidate with backgrounds in quantitative disciplines: applied mathematics, physics, computer science or engineering. Knowledge of biology, neuroscience and ability to work with data is highly desired.
Candidates will be trained in model building, analysis and will be offered advanced training in neuroscience and cognitive psychology. Candidates will have an opportunity to develop independent research projects and collaborations under the direction of the group leading scientists.
The TNG is a structural part of the HSE’s Centre for Cognition & Decision Making <https://www.hse.ru/en/cdm-centre/> with ample collaboration opportunities within the Centre with other research groups, both within Russia and internationally. This new international group is tightly linked with the Group for Neural Theory at the Ecole Normale Superior <http://iec-lnc.ens.fr/group-for-neural-theory/?lang=en> in Paris, where research internships and visiting positions can be made available.
Application Process
Applications must be submitted online. Please provide a CV, a statement of research interest and a recent research paper submitted via an online application form. At least two letters of recommendation should be sent directly to the International Faculty Recruitment Office at fellowship(a)hse.ru <mailto:fellowship@hse.ru> before the application deadline. Please note that direct applications to the hiring department may not be reviewed.
More information can be also obtained from boris.gutkin(a)hse.ru
Dec. 28, 2019
COSYNE 2020: Registration; Travel grants; Cosyne Tutorials
by Tomas Hromadka
====================================================
Computational and Systems Neuroscience 2020 (Cosyne)
MAIN MEETING
27 February - 01 March 2020
Denver, Colorado
WORKSHOPS
02 March - 03 March 2020
Breckenridge, Colorado
www.cosyne.org
====================================================
IMPORTANT DATES
Online registration is now open.
Travel grant submission is now open.
Travel grant application deadlines
*31 December 2019, 11.59PM PST (Undergraduate Travel Grant)*
14 January 2020, 11.59PM PST (Other travel grants)
-----------------------------------------------
TRAVEL GRANTS
-----------------------------------------------
Applications are now open for travel grants to attend the conference.
Each awardee will receive at least $500 to help offset the costs of
travel, registration, and accommodations. Larger grants may be available
to those traveling from outside North America. Special consideration is
given to scientists who have not previously attended the meeting,
under-represented minorities, students who are attending the meeting
together with a mentor, undergraduate students, and authors of submitted
Cosyne abstracts. We currently offer five travel grant programs for New
Attendees, Presenters, Mentors, Undergraduates, and Childcare travel
grants. For details on applying, see Cosyne.org -> Travel grants.
----------------------------------------------------
COSYNE TUTORIALS
----------------------------------------------------
Cosyne 2019 will host two tutorial sessions on 27 February 2020. For
details on Cosyne tutorials please visit Cosyne.org -> Tutorials 20.
Tutorial 1: Cosyne 2020 Tutorial session sponsored by the Simons
Foundation
Topic: Normative approaches to understanding neural coding and behavior
Speaker: Ann Hermundstad
Ann Hermundstad is a Group Leader in the Computation & Theory
research core at Janelia Research Campus. She studies how the brain
creates and uses adaptive sensorimotor representations to generate
flexible behavior. Her lab uses a combination of theory, modeling, and
data analysis to explore how neural circuits can do this efficiently and
flexibly, and works in close collaboration with experimentalists to test
these ideas in biological systems.
We are recruiting TAs for the tutorial session. If interested, please
see Cosyne.org -> Tutorials 20 for details on how to apply.
Tutorial 2
Topic: Neurodata without Borders Tutorial
NWB is a data standard for neurophysiology, providing neuroscientists
with a common standard to share, archive, use, and build common analysis
tools for neurophysiology data. Navigating the Allen Brain Observatory
----------------------------------------------------
BRIDGE TO INDEPENDENCE AWARD
----------------------------------------------------
The Simons Foundation Autism Research Initiative (SFARI) is invested in
supporting the next generation of top autism researchers. The Bridge to
Independence grant program promotes talented early-career scientists by
facilitating their transition to research independence and providing
grant funding at the start of their professorships
(https://www.sfari.org/2018/06/15/bridge-to-independence-award-request-for-a…)
----------------------------------------------------
COSYNE
----------------------------------------------------
The annual Cosyne meeting provides an inclusive forum for the exchange
of empirical and theoretical approaches to problems in systems
neuroscience, in order to understand how neural systems function.
The MAIN MEETING is single-track. A set of invited talks is selected by
the Executive Committee, and additional talks and posters are selected
by the Program Committee, based on submitted abstracts. The WORKSHOPS
feature in-depth discussion of current topics of interest, in a small
group setting. For details on workshop proposals please see below or
visit Cosyne.org -> Workshops.
Cosyne topics include but are not limited to: neural basis of behavior,
sensory and motor systems, circuitry, learning, neural coding, natural
scene statistics, dendritic computation, neural basis of persistent
activity, nonlinear receptive field mapping, representations of time and
sequence, reward systems, decision-making, synaptic plasticity, map
formation and plasticity, population coding, attention, and computation
with spiking networks.
This year we would like to foster increased participation from
experimental groups as well as computational ones. Please circulate
widely and encourage your students and postdocs to apply.
COSYNE INVITED SPEAKERS
Matthew Botvinick (Deepmind/Princeton)
Megan Carey (Champalimaud)
John Cunningham (Columbia)
Gul Dolen (Hopkins)
Rainer Friedrich (FMI Basel)
Sam Gershman (Harvard)
Lisa Giocomo (Stanford)
Christopher Harvey (Harvard)
Mehrdad Jazayeri (MIT)
Wei Ji Ma (NYU)
Hendrikje Nienborg (Tuebingen/NIH)
Linda Wilbrecht (Berkeley)
Marta Zlatic (Janelia)
ORGANIZING COMMITTEE
General Chairs: Eugenia Chiappe (Champalimaud) and Christian Machens
(Champalimaud)
Program Chairs: Anne-Marie Oswald (U Pittsburgh) and Srdjan Ostojic
(Ecole Normale Superieure Paris)
Workshop Chairs: Catherine Hartley (NYU) and Blake Richards (McGill)
Undergraduate Travel Chairs: Angela Langdon (Princeton) and Robert
Wilson (U Arizona)
Diversity Chairs: Eva Dyer (Georgia Tech, Emory) and Eric Shea-Brown
(U Washington)
Publicity Chair: Adam Calhoun (Princeton)
Development Chair: Michael Long (NYU)
EXECUTIVE COMMITTEE
Stephanie Palmer (U Chicago)
Zachary Mainen (Champalimaud)
Alexandre Pouget (U Geneva)
Anthony Zador (CSHL)
CONTACT
meeting [at] cosyne.org
----------------------------------------------------
COSYNE MAILING LISTS
----------------------------------------------------
Please consider adding yourself to Cosyne mailing lists (groups) to
receive email updates with various Cosyne-related information and join
in helpful discussions. See Cosyne.org -> Mailing lists for details.
Dec. 28, 2019
PhD Studentship in Neural Data Science, Computational Neuromodulation and Metalearning
by Wong-Lin, Kongfatt
Applications are invited for a Ph.D. studentship in Neural Data Science, Computational Neuromodulation and Metalearning, tenable in the Faculty of Computing, Engineering and the Built Environment at Ulster University, UK.
This PhD project is a collaboration between Ulster University and the University of Oxford (amongst other collaborators) on the computational modelling and theoretical development of neuromodulation in decision-making and learning. For more information, please refer to:
https://www.ulster.ac.uk/doctoralcollege/find-a-phd/512105
The application process for the Ph.D. studentship is opened with a closing date for applications on the 7th February 2020.
The computational and cognitive neuroscience research community at the Intelligent Systems Research Centre at Ulster University focuses on both fundamental brain and behavioural sciences, and their applications, including neuro-inspired AI, neural engineering and neurotechnology, and clinical neuroscience. The successful PhD candidate will be based at the Research Centre while interacting closely with collaborators at the University of Oxford and other international research institutes.
If you wish to discuss your application or enquire more about this Ph.D. studentship, please contact: Dr. KongFatt Wong-Lin (k.wong-lin(a)ulster.ac.uk<mailto:k.wong-lin@ulster.ac.uk>).
-------------------
Dr. KongFatt Wong-Lin
Intelligent Systems Research Centre
School of Computing, Engineering and Intelligent Systems
Faculty of Computing, Engineering and the Built Environment
Ulster University
Magee Campus
UK
https://www.ulster.ac.uk/staff/k-wong-lin
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Dec. 27, 2019
Funded PhD and Data scientist positions
by Abhishek Banerjee
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
Dec. 25, 2019
Announcing Okinawa/OIST Computational Neuroscience Course 2020
by Erik De Schutter
OKINAWA/OIST COMPUTATIONAL NEUROSCIENCE COURSE 2020
Methods, Neurons, Networks and Behaviors
June 29 to July 16, 2020
Okinawa Institute of Science and Technology Graduate University, Japan
https://groups.oist.jp/ocnc
The aim of the Okinawa/OIST Computational Neuroscience Course is to
provide opportunities for young researchers with theoretical backgrounds
to learn the latest advances in neuroscience, and for those with experimental
backgrounds to have hands-on experience in computational modeling.
We invite graduate students and postgraduate researchers to participate
in the course, held from June 29th through July 16th, 2020 at an oceanfront
seminar house of the Okinawa Institute of Science and Technology Graduate
University. Applications are through the course web page
(https://groups.oist.jp/ocnc) only; January 1 - February 2, 2020.
Applicants will receive confirmation of acceptance in March.
Like in preceding years, the 17th OCNC will be a comprehensive three-week
course covering single neurons, networks, and behaviors with ample time for
student projects. The first week will focus exclusively on methods with
hands-on tutorials during the afternoons, while the second and third weeks
will have lectures by international experts. The course has a strong hands-on
component based on student proposed modeling or data analysis projects,
which are further refined with the help of a dedicated tutor. Applicants are
required to propose their project at the time of application.
There is no tuition fee. The sponsor will provide lodging and meals during
the course and provides partial travel support. We hope that this course
will be a good opportunity for theoretical and experimental neuroscientists
to meet each other and to explore the attractive nature and culture of
Okinawa, the southernmost island prefecture of Japan.
Invited faculty:
• Michael Berry II (Princeton University, USA)
• Tiago Branco (Sainsbury Wellcome Centre, London, UK)
• Zenas C Chao (University of Kyoto, Japan)
• Erik De Schutter (OIST)
• Kenji Doya (OIST)
• Gaute Einevoll (Norwegian University of Life Sciences, Norway)
• Tomoki Fukai (OIST)
• Boris Gutkin (Ecole Normale Supérieure, Paris, France)
• Bernd Kuhn (OIST)
• Devika Narain (Erasmus Medical Center, Rotterdam, Netherlands)
• Alex Pouget (University of Geneva, Switzerland)
• Ivan Soltesz (Stanford University, USA)
• Saori C. Tanaka (ATR, Japan)
• Tatjana Tchumatchenko (Max Planck Institute for Brain Research, Frankfur, Germany)
• Marylka Yoe Uusisaari (OIST)
Dec. 23, 2019
NeuroBridges 2020 Summer School Announcement
by Ahmed El Hady
*/NeuroBridges 2020 Summer school , Cluny, France/*
*/( September 6th - September 17th, 2020)/*
*/
/*
I would like to bring to your attention the NeuroBridges 2020 Summer School
<http://decision-making-lab.com/NeuroBridges/neurobridges2020.html>
<http://decision-making-lab.com/NeuroBridges/neurobridges2020.html>
NeuroBridges <https://www.facebook.com/NeuroBridges/>is a one-of-a-kind
series of scientific meetings in brain research, which brings together
Mediterranean and Middle Eastern scientists, in order to promote
international scientific cooperation in system and computational
neuroscience. A major goal of this school is to serve as a bridge
between experimental and theoretical neuroscientists, addressing
system-level questions. This year the school will primarily focus on the
neural basis and computational principles underlying decision making.
*The forthcoming NeuroBridges 2020*will be a ten-day summer school.
Students will attend lectures delivered by a group of leading
neuroscientists, experimentalists as well as theoreticians, which will
address the fundamental questions in the field of decision making. In
addition to the lectures, the students will work in groups on small
research projects.
The school is intended for graduate students and postdocs, primarily
(but not only) from the Middle East and the Mediterranean region either
working in their home countries or abroad. We will consider applicants
with some background in related fields in neuroscience or cognitive
psychology.
Through the online application system, you will be asked to provide
personal details, academic background, a motivation letter that should
include a paragraph about your quantitative skills and a CV. In
addition, we request two recommendation letters.
The school will take place between *September 6 and September 17, 2020*
in Le Centre de Conferences Internationales de Cluny (CCIC)
<http://www.ccic.eu/index.html>. Cluny is a small medieval town in
Burgundy, France, located about 400km southeast of Paris (accessible by
fast train, TGV).
All costs of registration and accommodation will be covered by the
organizers. A limited number of travel grants will also be available.
*NeuroBridges* is co-organized by Ahmed El Hady
<http://scholar.princeton.edu/ahmedelhady/home> (Princeton Neuroscience
Institute, USA), Yonatan Loewenstein
<http://elsc.huji.ac.il/loewenstein/home>(Hebrew University of
Jerusalem, Israel) and David Hansel
<https://neurophys.biomedicale.parisdescartes.fr/members/david-hansel/> (CNRS,
Paris, France).
Review of applications will end in May 2020.
*2020 Faculty:*
Carlos Brody (Princeton) <https://pni.princeton.edu/faculty/carlos-brody>
Ahmed El Hady (Princeton) <http://scholar.princeton.edu/ahmedelhady/home>
David Hansel (CNRS)
<https://neurophys.biomedicale.parisdescartes.fr/members/david-hansel/>
Ifat Levy (Yale) <https://medicine.yale.edu/profile/ifat_levy>
Yonatan Loewenstein (Hebrew U.)
<https://elsc.huji.ac.il/faculty-staff/yonatan-loewenstein>
Najib Majaj (NYU) <https://www.researchgate.net/profile/Najib_Majaj>
Mike Shadlen (Columbia U.)
<https://neuroscience.columbia.edu/profile/michaelshadlen>
Eyal Winter (Hebrew U.) <http://www.ma.huji.ac.il/%7Emseyal/>
Yoram Yovell (Hadassah Hebrew U. Medical Center) <http://yovell.co.il/en/>
The deadline for application is *April 1st, 2020 *and the following is
the website including the link for the online application:
http://decision-making-lab.com/NeuroBridges/neurobridges2020.html
<http://decision-making-lab.com/NeuroBridges/neurobridges2019.html>
<http://decision-making-lab.com/NeuroBridges/neurobridges2019.html>
For more information, please contact neurobridges2020(a)gmail.com
<mailto:neurobridges2018@gmail.com>.
Dec. 22, 2019
Call for Papers: Workshop on Machine Learning and Computational Intelligence in multi-omics and medical image analysis, 5-7 June, Greece
by Tiago Azevedo
Dear all,
Below find the call for papers for the workshop "Machine Learning and Computational Intelligence in multi-omics and medical image analysis (MALCI_MUOMI 2020)".
It will be held during the 2020 AIAI conference, collocated with EANN 2020, the 21st International Conference on engineering Applications of Neural Networks. This will be held 5-7 June 2020, Porto Carras Grand Resort, Halkidiki Greece.
**Important Dates**
Paper Submission Deadline: 29th of February 2020
Notification of Acceptance/Rejection: 22nd of March 2020
Camera Ready Submission/Registration: 2nd of April 2020
Early / Author registration by: 2nd of April 2020
Conference Dates: 5-7 June, 2020
**Link for submissions**
http://www.aiai2020.eu/malci_muomi2020/#submission
**Aim and scope**
There is an increasing need for the application of Machine Learning (ML) and Computational Intelligence (CI) techniques, which can effectively perform image processing operations (such as segmentation, co-registration, classification, and dimensionality reduction), in the fields of neuroimaging and oncological imaging. Although the manual approach often remains the golden standard in some tasks (e.g., segmentation), ML can be exploited to automate and facilitate the work of researchers and clinicians. Frequently used techniques include Support Vector Machines (SVMs) for classification problems, graph-based methods, and Artificial Neural Networks (ANNs).
More recently, deep ANNs have shown to be very successful in computer vision tasks owing to the ability to automatically extract hierarchical descriptive features from input images. It has also been used in the oncological and neuroimaging domains for automatic disease diagnosis, tissue segmentation, and even synthetic image generation. The main issue, however, remains the relative sample paucity of the typical imaging datasets that leads to a poor generalisation of the employed deep ANNs, considering the high number of required parameters. Consequently, parameter-efficient design paradigms, specifically tailored to medical applications, ought to be devised, also by exploiting CI-based techniques (e.g., neuroevolution).
In this context, these advanced ML techniques can be suitably exploited to combine heterogeneous sources of information, allowing for multi-omics data integration. Such a kind of analyses may represent a significant step towards personalised medicine.
Topics of interest include but are not limited to:
· ML techniques for segmentation, co-registration, classification, or dimensionality reduction of medical images
· Deep neural networks for medical image super-resolution, de-noising and synthesis
· Deep Learning for neuroimaging and oncological imaging analysis
· Integration of multi-omics data
· Brain network analysis
· Application of graph theory to MRI and functional MRI (fMRI) data
· Application of ML methods for neurodegenerative disease studies
· Computational modelling and analysis of neuroimaging
· Methods of analysis for structural or functional connectivity
· Development of new neuroimaging tools
· Radiomic analyses for tumour phenotypes
· Radiogenomics for intra- and inter-tumoural heterogeneity evaluation
· Generative adversarial models for data augmentation and image super-resolution
· CI methods for optimizing medical image analysis tasks
**Workshop Organizing Committee**
Tiago Azevedo – Department of Computer Science and Technology , University of Cambridge, Cambridge, (UK)
Giovanna Maria Dimitri – Department of Computer Science and Technology , University of Cambridge, Cambridge (UK), Department of Medicine, University of Siena (Italy)
Prof Pietro Liò – Department of Computer Science and Technology , University of Cambridge, Cambridge, (UK)
Dr Leonardo Rundo – Department of Radiology, University of Cambridge, Cambridge (UK )
Simeon Spasov – Department of Computer Science and Technology , University of Cambridge, Cambridge (UK)
Dr Andrea Tangherloni – Department of Haematology, University of Cambridge, Cambridge, (UK)
Jin Zhu – Department of Computer Science and Technology , University of Cambridge, Cambridge, UK
Dec. 22, 2019