- Comp-neuro - lists.cnsorg.org

Openings for Postdocs, RAs, and PhD Students in Computational Psychiatry and Neuro-AI (Lin Lab)

by doerlbh＠gmail.com

Dear colleagues, The Lin Lab (Bytes of Minds Lab) at Mount Sinai is actively recruiting Postdoctoral Researchers, PhD Students, and Research Assistants passionate about Computational Psychiatry and Neuro-AI. Led by Dr. Baihan Lin and based within New York’s largest health network, our lab is at the forefront of mental health technology and brain-inspired AI research, combining insights from neuroscience, cognitive science, and machine learning to create adaptive, intelligent systems that can transform mental health care and deepen our understanding of the mind. Why Join Us? - Cutting-edge Research: Our work spans neuro-inspired AI, computational psychiatry, brain-computer interfaces, extended realities (XR), social media analysis, wearable technology, and more. - Interdisciplinary Environment: Engage with advanced neuroscience, machine learning, and cognitive science to create innovative tools for mental health and next-gen neurotechnology. - Unique Positioning: As part of Mount Sinai’s dynamic research community, we have access to extensive data resources and collaborations within a top-tier hospital network, biggest in NY, and ranked #1 in healthcare AI by Nature. We invite interested candidates with a drive to explore the frontiers of mind and machine to join us. For more details, visit linlab.org, or apply directly by emailing Dr. Baihan Lin at baihan.lin(a)mssm.edu. US (and especially NYC-based) candidates preferred, though international applicants are welcome to apply. Best, Baihan Lin, PhD Bytes of Minds Lab (Lin Lab) Departments of AI, Psychiatry, and Neuroscience Hasso Plattner Institute for Digital Health, Friedman Brain Institute, Center for Computational Psychiatry Icahn School of Medicine at Mount Sinai, New York, NY, USA baihan.lin(a)mssm.edu | linlab.org

Nov. 1, 2024

Invitation to EiNS Seminars: Guillermo Cecchi (IBM Research, USA) - AI Challenges for Large Longitudinal Clinical Trials in Mental Health

by Jose A. Fernandez

Dear Comp-Neuro members, You're cordially invited to join us for the upcoming session of the “Explorations in Neuroscience Seminars” (EiNS). We are excited to feature *Guillermo Cecchi* from the *T.J. Watson Institute at IBM Research, USA*, who will be presenting on “*AI Challenges for Large Longitudinal Clinical Trials in Mental Health.*” The lecture will take place on YouTube Live on *Friday, November 15, 2024, at 3 PM (GMT-3)*. We look forward to your participation! Please note that this talk will be conducted in Spanish. Feel free to share this invitation with anyone who might be interested but isn't on our list. *Link:* https://www.youtube.com/ExactasUNCPBA/live Best wishes, *Jose A. Fernandez-Leon Fellenz*Adjunct Professor UNCPBA - Researcher CONICET CIFICEN (UNCPBA-CICPBA-CONICET) & INTIA (UNCPBA-CICPBA) Dept. of Computer Science and Systems - Exactas-UNCPBA *EMail:* jafernandez(a)intia.exa.unicen.edu.ar *Web:* https://jafphd.intia.exa.unicen.edu.ar/ *NeuroAI Lab:* https://neuro-ai-lab.intia.exa.unicen.edu.ar/ ---------------------- *Title: AI Challenges for Large Longitudinal Clinical Trials in Mental Health - * *Guillermo Cecchi (Institute T.J. Watson – IBM Research, USA)* *Abstract: *The recent experience of accelerated vaccine development under the pressure of the covid pandemic, the massive adoption of consumer electronics and the explosion of AI capabilities signal a dramatic shift in the implementation of clinical trials, which have been particularly ineffective and onerous in mental health. We will present results from ongoing and recently completed large longitudinal clinical trials for Amyotrophic Lateral Sclerosis (ALS), Chronic Pain, Prodromal Psychosis and outcomes across all mental health conditions in which massive streams of clinical data are combined with at-home ultra-high frequency digital information including smart phone use, geolocation, and semi-structured and free-form language to provide a holistic and quasi-real time assessment of the participants, and will discuss the analytic and interpretation challenges that emerge in these demanding studies. *BIO:* https://research.ibm.com/people/guillermo-cecchi *Academic background:* Guillermo Cecchi received an education in Physics (MSc, University of La Plata, Argentina, 1991), Physics and Biology (PhD, The Rockefeller University, 1994-1999), and Imaging in Psychiatry (Postdoctoral Fellow, Cornell University 2000-2001). He has been interested in diverse aspects of theoretical biology, including Brownian transport, molecular computation, spike reliability in neurons, song production and representation in songbirds, statistics of natural images and visual perception, statistics of natural language, and brain imaging. In 2001 he joined IBM Research to work on computational approaches to brain function. In recent years, Dr. Cecchi has pioneered the use of a computational linguistics approach to quantify psychiatric conditions from short speech samples, applying it successfully to conditions as diverse as schizophrenia, mania, prodromal psychosis, chronic pain, neurodegeneration, drug and alcohol intake, and psychotherapy. *Areas of research: *Dr. Cecchi directs the Computational Psychiatry and the Neuroimaging groups in IBM Research, and is Associate Director of Analytics for NIH's Advancing Medicines Partnerships - Schizophrenia. From May 2024, Dr. Cecchi is the co-Director of the PREDiCT Center for outcomes forecast across all mental health outpatients in New York City Mt Sinai hospitals (NIH U01 center grant). *About EiNS Seminars*: This online seminar series aims to go beyond the human mind to unlock intelligence across nature and machines. The talks invite a cross-disciplinary exploration of cognitive and decision-making systems, and computational linguistics from biological organisms to Artificial Intelligence. By examining the intricacies of minds embedded in physical bodies or their absence, we aim to uncover novel approaches for developing neuroscience and artificial intelligence. Join us as we delve into the fascinating world of embodied and cognitive intelligence, exploring how memory, learning, decision-making, environmental awareness, and consciousness manifest across various life forms and AI challenges. Each talk will feature captivating case studies and open dialogue, fostering a collaborative environment for generating fresh perspectives. The talks are recorded only with authorization of the speaker and are available to everybody at https://neuro-ai-lab.intia.exa.unicen.edu.ar/eins-seminars.

Oct. 30, 2024

Complex Networks 2024 – Program & Registration now Available!

by Hocine Cherifi

We’re thrilled to invite you to Complex Networks 2024! The program is now live, featuring an exceptional lineup of keynote speakers, tutorials, presentations, and sessions that showcase the latest developments in complex networks. *Explore the Program:* Our diverse schedule includes thought-provoking keynotes, hands-on tutorials, oral presentations, and interactive poster and lightning sessions. You can view the full program here: [Link to All Files <https://drive.google.com/drive/folders/1gEuIWHM5NXkd75Q3fun5zuTyp-lbFu_o?us…> ]. *Key Highlights:* - *Tutorials <https://complexnetworks.org/tutorials/> on December 09:* Join specialized tutorials designed to deepen your knowledge and provide practical skills. - *Keynote Speakers <https://complexnetworks.org/keynotes/>:* Gain insights from renowned experts who will share cutting-edge perspectives on complex network research and applications. - *Program at a Glance <https://drive.google.com/file/d/1paPlcRaZmntRoToxc5Rbq8YampNlNLP2/view>* - *Poster Sessions <https://drive.google.com/file/d/1fWZkkYijpASQwZHJfCc5RtnikUwmFCCF/view>* - *Oral Sessions <https://drive.google.com/file/d/1MwPeu5RdoCPPbdp_8zmslmOfwK735ewZ/view>* - *Lightning Sessions <https://drive.google.com/file/d/12iZxpGrjcJwMCN4K6gDqkGagWFIEyjkG/view>* *Register Now:* Don’t miss the opportunity to engage with leading researchers and practitioners in the field. If you haven’t registered yet, secure your spot here: [https://complexnetworks.org/registration/] <https://complexnetworks.org/registration/> *Conference Dates and Location:* Conference will be held from December 10, 2024 to December 12, 2024 in vibrant Istanbul. In addition to the sessions, enjoy networking opportunities, including a welcome reception and a gala dinner, to foster collaboration and connection. We look forward to seeing you in Istanbul for an enriching and inspiring event! Best regards, Complex Networks 2024 Organizing Committee Join us at COMPLEX NETWORKS 2024 <https://www.complexnetworks.org/> *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comté Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Editor in Chief Plos Complex Systems <https://plos.org/complex-systems-research-journal/#:~:text=PLOS%20Complex%2….> Founding & Adisory Editor Applied Network Science <https://appliednetsci.springeropen.com/> Editorial Board member PLOS One <https://journals.plos.org/plosone/>, IEEE ACCESS <https://ieeeaccess.ieee.org/?http%3A%2F%2Fieeeaccess_ieee_org%2F>, Scientific Reports <https://www.nature.com/srep/>, Journal of Imaging <https://www.mdpi.com/journal/jimaging>, Quality and Quantity <https://www.springer.com/journal/11135/>, Computational Social Networks <https://computationalsocialnetworks.springeropen.com/>, Complex Systems <https://www.complex-systems.com/>

Oct. 30, 2024

Two PhD positions

by Phil Garner

Dear Colleagues, The Idiap Research Institute in partnership with the Department of Mathematics at Mahidol University seek two PhD students to work on Bayesian Optimisation and training techniques for spiking neural networks. Funded by the Swiss NSF, one student will be based in Martigny in the Swiss alps, the other in Bangkok in Thailand. Exchanges between the two are planned. In addition to promising better understanding of biological processes, spiking nets have persuasive low-power implications. However, they present difficulties associated with their many hyperparameters, binary nature and non-differentiability of the emitted spikes. At Idiap, the project will build on our recent work that has shown that spiking networks are plausible solutions for speech processing tasks. The Bayesian approach will be twofold: In a first thread we will attempt to show that prior information can compensate for discontinuities in the error landscape arising from the binary nature. In a second thread, we will use Bayesian Optimisation techniques to handle the increased number of hyperparameters associated with spiking neurons. At Mahidol, the team will be responsible for designing frameworks for LPNet and neural networks to address the vehicle routing problem (VRP). The project will explore the effectiveness of these approaches in solving VRP and identify their limitations. The ultimate aim is to enhance VRP solutions through our spiking neural network (SNN) framework. The ideal student should have a master's (or equivalent) degree in engineering, computer science, physics, or mathematics. They should have a good background in mathematics, statistics, and programming (C/C++, Python, scripting languages). Candidates should have a deep understanding of ANNs and, ideally, familiarity with SNNs. For more information and to apply, for Idiap: https://careers.werecruit.io/en/idiap/offers/phd---bayesian-methods-for-spi… for Mahidol: https://mathematics.sc.mahidol.ac.th/scholarship-for-phd-in-mathematics-swi… The SNSF SPIRIT program is especially concerned with gender and identity inclusivity; we will emphasize this through the hiring process. In this sense, we particularly encourage applications from female candidates. Sincerely, -- Phil Garner http://www.idiap.ch/~pgarner

Oct. 30, 2024

PhD opportunity: computational neuroscience of decision-making and addiction

by mailinglists.4svr4＠simplelogin.com

I am seeking candidates for a potential PhD project at the University of Surrey, investigating how dopamine shapes memory formation and decision-making in healthy and addictive behaviours. Essential Requirements * Strong academic background * Programming skills (or strong willingness to learn) * Advanced statistical knowledge (or strong willingness to learn) * Interest in computational neuroscience and addiction research Funding Information Through the South East Doctoral Training Arc (SEDarc), funded by the Economic and Social Research Council (ESRC), successful candidates can receive: * Full funding for UK or International students * Living stipend at UKRI rates * Access to advanced research training Previous students from our School have successfully secured these competitive studentships. However, funding is not guaranteed and depends on both the candidate's academic excellence and the strength of the research proposal. If you are interested, please send your CV to c.feherdasilva(a)surrey.ac.uk . I will be happy to discuss the project idea and guide you through the application process. Best regards, Carolina Feher da Silva Lecturer in Psychology University of Surrey Note: This opportunity is open to both UK and International students. The University of Surrey is located in Guildford, 40 minutes from central London.

Oct. 29, 2024

Queers in STEM social London

by Niedernhuber,Maria

Dear all Representatives of LGBT university staff networks in London, as well as the organisation Pride in STEM, are organising a social for queer academics, focusing on STEM. Anyone is welcome. Since our social originated at a cognitive and computational neuroscience conference, queer neuroscientists are very well represented, and we hope that this will be a great opportunity to network for queer people in cognitive and computational neuroscience. This is the sign-up link: <https://www.outsavvy.com/event/23202/queers-in-stem-pub-social> https://www.outsavvy.com/event/23202/queers-in-stem-pub-social. If anyone here is interested in co-organising, please shoot me an email, and feel free to forward the sign-up link to anyone you know who might be interested. We are especially still looking for a contact person at the University of Greenwich and at Royal Holloway University of London, which are not represented in the organising team at the moment, to advertise the social in their local LGBT staff network. Feel free to email me to chat about the initiative, and how to get involved! Have a lovely week! Maria (they/them) --- Maria Niedernhuber Postdoctoral researcher in Cognitive Neuroscience Consciousness and Cognition Lab, University of Cambridge Sleep and Cognition Lab, QMUL

Oct. 29, 2024

[Newsletter] rTAIM Seminar #13 | Ethical Agent or Mere Tool?: A Cautioning Argument for “Moral” Artificial Intelligence in Healthcare | 30 October 2024, 15h00, Online

by steven gouveia

rTAIM (Rebuilding Trust in AI Medicine) Monthly Seminars Seminar #13 Ethical Agent or Mere Tool?: A Cautioning Argument for “Moral” Artificial Intelligence in Healthcare Jordan Joseph Wadden (Unity Health Toronto - Canada) Following the 12th rTAIM Online Seminar (by Francesco Prinzi, University of Palermo), we are happy to announce the first seminar of this academic year 2024/2025, the 13th rTAIM Online Seminar, with the participation of Jordan Joseph Wadden (Unity Health Toronto, Canada), on the 30th October 2024, 15h00-16h30 Lisbon Time Zone, via Zoom. ONLINE | Link Zoom<https://videoconf-colibri.zoom.us/j/95294324802?pwd=Lt2o4boR0iHYWFtXvu6KdrD…> ID: 952 9432 4802 | Password: 506705 #Seminar 13: To talk of moral machines presupposes that researchers understand enough about how humans come to their own conceptions of the good. Moral epistemology and moral psychology have struggled to describe these facts and processes, and we still don’t have a generalizable conception. However, there appears to be an assumption that ethics can nonetheless be instilled directly into artificial intelligence. This is of special concern in healthcare because algorithms and systems are being designed to recommend treatments and pathways for patients. But finding the right treatment for a patient requires more than just an analysis of the medical facts. Healthcare teams must also weigh preferences, goals, psycho-social needs, religious and spiritual beliefs, quality of life, and so on. Each of these elements has a unique, and often individualized, moral element. This paper presents an argument that healthcare artificial intelligence ought to be viewed as a mere tool, rather than as a (quasi-)moral agent which could act alone in the clinical encounter. I argue that some researchers have become distracted by the AI and robot rights discussions, making them think it’s possible to code ethics into a system when humans still don’t understand how we come to believe our own moral beliefs. Short Bio: Jordan Joseph Wadden, MA, PhD, HEC-C, is a clinical ethicist at Unity Health Toronto in Canada. He is an assistant professor (status only) in the Department of Family and Community Medicine at the University of Toronto. His research focuses on the ethical implementation of artificial intelligence and machine learning in healthcare. He was the winner of the 2024 Ethics of AI Award at the 3rd International Conference on the Ethics of Artificial Intelligence. rTAIM Seminars: https://ifilosofia.up.pt/activities/rtaim-seminars https://trustaimedicine.weebly.com/rtaim-seminars.html Organisation: Steven S. Gouveia (MLAG/IF) Mind, Language and Action Group (MLAG) Instituto de Filosofia da Universidade do Porto – UIDB/00502/2020 Fundação para a Ciência e a Tecnologia (FCT) ____________________________________________ Instituto de Filosofia (UI&D 502) Faculdade de Letras da Universidade do Porto Via Panorâmica s/n 4150-564 Porto Tel. 22 607 71 80 E-mail: ifilosofia(a)letras.up.pt<mailto:ifilosofia@letras.up.pt> http://ifilosofia.up.pt/

Oct. 28, 2024

NIH-funded Post-doctoral fellowship - spatial navigation, gait, mobility, EEG, MRI, virtual reality - in biomedical engineering at the University of Florida

by Steve Weisberg

A postdoctoral researcher position studying electrocortical activity during human navigation is available in the laboratory of Dr. Daniel Ferris ( https://faculty.eng.ufl.edu/human-neuromechanics-laboratory) This position is for an initial one-year appointment, and has the potential to be renewed for three additional years based on performance and funding availability. https://explore.jobs.ufl.edu/cw/en-us/job/533572/postdoc Join a team studying age- and ADRD-related changes in gait and navigation, including Rachael Seidler, Dan Ferris, and Steve Weisberg. -- --------------------------------------------- *Steven M. Weisberg, PhD * Pronouns: he/him/his Assistant Professor of Psychology University of Florida Director: SCANN Lab <http://scannlab.psych.ufl.edu>

Oct. 28, 2024

[comp-neuro] job advertisement | 1 fully funded PhD position (E13) | Application deadline: Nov.18, 2024

by Daniel Schmid

Vacancy for dissertation/PhD project *Learning Search and Decision Mechanisms in Medical Diagnosis* We are looking for a new PhD student for a fully funded interdisciplinary research project investigating the computational mechanisms underlying the perceptual processes in medical imaging. *Brief project description and goals* Medical experts routinely screen images for signs of abnormality indicative of a disease. Experimental evidence shows that these experts, based on their training, are able to make a diagnose above chance level even after screening images for only a few seconds. Such visual inspection utilizes global ensemble scene statistics, or “scene gist”, to provide contextual guidance information. The goal of the PhD project is to investigate how such global, contextual gist information can be computed and incorporated in machine vision approaches, such as deep neural networks for natural or medical image processing. In particular, a goal is to develop neural mechanisms that can be integrated into existing pre-trained CNNs to compute scene gist for rapid global decision-making and contextual guidance in medical images. Such mechanisms should explain how such global feature compositions are learned to increase the classification specificity and, at the same time, do not equip an observer with the ability to precisely localize such feature compositions indicative of the evidence. At the implementation level, computational units (neurons) in hierarchical CNN architectures will be extended by integrating local bottom-up feature extraction mechanisms with top-down modulatory contextual fields. We focus on these mechanisms to learn the integration of information streams in counter-stream networks by employing novel two-point information integration units inspired by recent findings from neuroscience. These investigations will contribute to develop novel CNN architectures by integrating feedforward and feedback data streams that operate at different spatio-temporal scales and feature types inspired by computational mechanisms in biological vision. The combined global and local information is expected to provide more detailed explanations on a mechanistic level how radiologists steer their attention and search capacities and learn to improve such skills. *Requirements* - MSc degree in Computer Science, Engineering, Physics, Mathematics, Cognitive Systems/Science or equivalent relevant background - Experience in computational vision, neural networks, machine learning; with strong mathematical/physics foundation - Experience in developing biologically inspired models – or interested in learning how to develop such mechanisms and models - Experience in analysis of large data and evaluation of results - Strong coding skills - Personal skills: working in a team, but should be able to work independently, is strongly focused and enthusiastic about the project theme, is self-motivated and takes responsibility for reaching milestones - Experience and talent in scientific writing (with proficient written & oral English) *Contact & application* The project is part of the newly founded research training group “KEMAI” that focuses on integrating knowledge and learning based approaches for better medical AI (https://kemai.uni-ulm.de/ for more information). The offered PhD position is fully funded (E13 salary) and also benefits from an interdisciplinary setting, the ability to connect with peers from related projects and a clearly structured PhD program. Application materials are expected until November 18, 2024. They should contain a CV, statement of research interest and background in relation to the KEMAI training group and project theme C2. A cover letter should inform about the expected date of availability and name of two referees. Submit your application via the KEMAI website (preferred) or to Prof. Heiko Neumann (heiko.neumann(a)uni-ulm.de) or reach out for more information. Best regards, Daniel Schmid -- Daniel Schmid, M.Sc. Institute of Neural Information Processing Faculty of Engineering, Computer Science and Psychology Ulm University James-Frank-Ring D-89081 Ulm Germany e-mail: daniel-1.schmid(a)uni-ulm.de

Oct. 28, 2024

Justin Wood speaking on November 12 in Developing Minds global online lecture series

by Jochen Triesch

Dear colleagues, On November 12, the Developing Minds global online lecture series is proud to host Justin Wood from Indiana University Bloomington, USA, speaking on: "Radical empiricism: The origins of knowledge as a mini-evolution“ Tuesday, November 12, 2024 9:00 am EST (Eastern Standard Time, US) 14:00 UTC (Universal Coordinated Time) 15:00 CET (Central European Time) 23:00 JST (Japan Standard Time) The zoom link/credentials are: https://uni-frankfurt.zoom-x.de/j/62980753356?pwd=0J6BtOaAy20YyanXX1gpkB3Ta… Meeting-ID: 629 8075 3356 Kenncode: 904159 Abstract: What are the origins of knowledge? A common theoretical strategy is to isolate core primitives of the mind, such as systems for reasoning about objects, space, number, agents, and language. The problem with this strategy is it disconnects brain development from general fitting principles that underlie chemistry, evolution, culture, and artificial intelligence. I argue that development can be understood as a “mini-evolution,” in which core mental skills are the products of generic evolution-like fitting processes. In evolution, life started from scratch, and species emerged as DNA adapted to the world via blind fitting. Likewise, in development, knowledge starts from scratch, and mental skills emerge as individual brains adapt to the world via blind fitting. Historically, the main roadblock for testing fitting theories has been the lack of benchmarks and models for measuring whether fitting models learn like brains. To directly compare learning across brains and models, both must be trained with the same data and tested on the same tasks. We propose a solution—called “Newborn Embodied Turing Tests” (NETTs)—in which newborn animals and fitting models are reared in the same environments and tested with the same tasks. I’ll describe a series of NETTs showing that generic fitting models (transformers) develop many core mental skills, including orientation selectivity, visual binding, shape-based vision, invariant object recognition, imprinting, collective behavior, and social preferences. These skills develop spontaneously when generic fitting models fit to prenatal and postnatal experiences. There is no need to postulate mysterious core primitives to explain the rapid development of domain-specific knowledge. Rather, core knowledge can be the product of generic fitting machinery: a radical empiricist view of the origins of knowledge. This mini-evolution view unifies chemistry, evolution, development, culture, and artificial intelligence under a common fitting framework, with shared general principles. Short Bio: Justin Wood is an Associate Professor of Informatics at Indiana University Bloomington. He is affiliated with programs in Animal Behavior, Neuroscience, Cognitive Science, and Psychological & Brain Sciences. He received his B.A. from University of Virginia and M.S. & Ph.D. from Harvard University. Dr. Wood has studied the psychological abilities of a range of populations, including human adults, children, infants, chimpanzees, wild monkeys, starlings, and newborn chicks. He works at the intersection of developmental psychology, neuroscience, virtual reality, and artificial intelligence to characterize the origins and computational foundations of intelligence. The talk will be recorded and made available for later viewing. For more information on the talk series and recordings of previous events, please visit: https://sites.google.com/view/developing-minds-series/home Best regards, Jochen Triesch -- Prof. Dr. Jochen Triesch Johanna Quandt Chair for Theoretical Life Sciences Frankfurt Institute for Advanced Studies and Goethe University Frankfurt http://fias.uni-frankfurt.de/~triesch/ Tel: +49 (0)69 798-47531 Fax: +49 (0)69 798-47611

Oct. 28, 2024