- Comp-neuro - lists.cnsorg.org

Call for Papers: Machine Learning Algorithms for Brain Imaging
by Shailesh Appukuttan 20 Jun '24

20 Jun '24

Dear colleagues, We invite researchers, neuroscientists, and machine learning experts to contribute to our Research Topic "*Machine Learning Algorithms for Brain Imaging: New Frontiers in Neurodiagnostics and Treatment*". Accepted articles will be published in the journal Frontiers in Neuroinformatics. https://www.frontiersin.org/research-topics/62418/machine-learning-algorith… *Submissions now open! * Manuscript Submission Deadline: 15 September 2024 Feel free to contact me for further info. This Frontiers Research Topic focuses on, but not limited to, the following themes: - Development and validation of novel machine learning algorithms for brain image analysis. - Deep learning techniques for brain image segmentation, classification, and feature extraction. - Predictive modeling and prognostication using machine learning to guide neurotherapeutic decisions. - Transfer learning and domain adaptation approaches in neuroimaging analysis. - Explainable AI and interpretable machine learning methods for transparent and trustworthy brain image interpretation. - Integration of multimodal imaging data (e.g., MRI, fMRI, PET) through innovative machine learning strategies. - Evaluation and benchmarking of machine learning algorithms in neuroimaging. - Current challenges, future directions, and ethical considerations in the application of machine learning algorithms in brain imaging. We welcome original research articles, comprehensive reviews, and perspectives that contribute to the field of machine-learning algorithms for brain imaging. Manuscripts should present novel methodologies, rigorous validation, and practical applications. Cheers, Shailesh Appukuttan Shailesh APPUKUTTAN *RECHERCHE > INT* Aix-Marseille Université - Campus Timone, INT NEUROSCIENCES,27 Boulevard Jean Moulin, Marseille, 13005 Site : https://shailesh-appukuttan.com/ - Email : shailesh.APPUKUTTAN(a)univ-amu.fr *Afin de respecter l'environnement, merci de n'imprimer cet email que si nécessaire.*

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Submit Your Research for COMPLEX NETWORKS 2024 in Istanbul!
by Hocine Cherifi 20 Jun '24

20 Jun '24

13 *th **International Conference on Complex Networks & Their Applications* Istanbul, Turkey December 10 - 12, 2024 COMPLEX NETWORKS 2024 <https://complexnetworks.org/> You are cordially invited to submit your contribution until *September 03, 2024*. *----------------------------------------------------------------------------------------------------------------------------------------------* *KEYNOTE SPEAKERS* · Federico Battiston <https://people.ceu.edu/federico_battiston> Central European University, Austria · Tina Eliassi-Rad <https://www.khoury.northeastern.edu/people/tina-eliassi-rad/> Northeastern University, USA · Frank Emmert-Streib <https://www.tuni.fi/en/frank-emmert-streib> Tampere University, Finland · Filippo Menczer <https://cnets.indiana.edu/fil/> Indiana University, USA · Luciano Pietronero <http://www.lucianopietronero.it/> University of Rome, Italy *----------------------------------------------------------------------------------------------------------------------------------------------* *TUTORIALS (December 09, 2024)* · Alessandro Galeazzi <https://scholar.google.com/citations?user=DK0tXAIAAAAJ&hl=en> University of Padova, Italy · Clara Stegehuis <https://www.clarastegehuis.nl/> Twente University, The Netherlands *----------------------------------------------------------------------------------------------------------------------------------------------* *CONTRIBUTIONS* *Full papers: *not previously published up to 12 pages · *Papers *will be included in the conference *proceedings edited by Springer* *Extended Abstracts*: about published or unpublished research up to 4 pages . · *Extended abstracts* will be published in the *Book of Abstracts (with ISBN)* · *https://cmt3.research.microsoft.com/COMPLEXNETWORKS2024/* <https://cmt3.research.microsoft.com/COMPLEXNETWORKS2024/> *----------------------------------------------------------------------------------------------------------------------------------------------* *JOURNAL SPECIAL ISSUES* *Extended versions of accepted contributions will be invited for publication in special issues of :* o PLOS Complex Systems <https://journals.plos.org/complexsystems/> edited by PLOS <https://plos.org/>. o PLOS <https://journals.plos.org/plosone/> One <https://journals.plos.org/plosone/> edited by PLOS <https://plos.org/> o Applied Network Science <https://appliednetsci.springeropen.com/> edited by Springer Nature <https://www.springernature.com/gp> o Social Network Analysis and Mining <https://link.springer.com/journal/13278> edited by Springer Nature <https://www.springernature.com/gp> o Computational & Mathematical organization <https://link.springer.com/journal/10588> edited by Springer Nature <https://www.springernature.com/gp> o Advances in Complex Systems <https://www.worldscientific.com/toc/acs/24/02> edited by World Scientific <https://www.worldscientific.com/> o Complex Systems Journal <https://www.complex-systems.com/> *Invitation Notification: December 18,2024* *Submission Deadline: February 28,2025* *----------------------------------------------------------------------------------------------------------------------------------------------* *SUBMISSION* *Refer to **https://complexnetworks.org/submission/* <https://complexnetworks.org/submission/> *----------------------------------------------------------------------------------------------------------------------------------------------* *TOPICS* *Topics include, but are not limited to: * o Models of Complex Networks o Structural Network Properties and Analysis o Complex Networks and Epidemics o Community Structure in Networks o Community Discovery in Complex Networks o Motif Discovery in Complex Networks o Network Mining o Network embedding methods o Machine learning with graphs o Dynamics and Evolution Patterns of Complex Networks o Link Prediction o Multilayer Networks o Network Controllability o Synchronization in Networks o Visual Representation of Complex Networks o Large-scale Graph Analytics o Social Reputation, Influence, and Trust o Information Spreading in Social Media o Rumour and Viral Marketing in Social Networks o Recommendation Systems and Complex Networks o Financial and Economic Networks o Complex Networks and Mobility o Biological and Technological Networks o Mobile call Networks o Bioinformatics and Earth Sciences Applications o Resilience and Robustness of Complex Networks o Complex Networks for Physical Infrastructures o Complex Networks, Smart Cities and Smart Grids o Political networks o Supply chain networks o Complex networks and information systems o Complex networks and CPS/IoT o Graph signal processing o Cognitive Network Science o Network Medicine o Network Neuroscience o Quantifying success through network analysis o Temporal and spatial networks o Historical Networks *-----------------------------------------------------------------------------------------------------------------------------------------* For further information and inquiries, please contact us at info(a)complexnetworks.org 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/>

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Postdoc position available
by Goodhill, Geoffrey 17 Jun '24

17 Jun '24

POSTDOC POSITION IN DECODING AUTISM SPECTRUM DISORDERS FROM MOVEMENT A postdoc position is available in the lab of Geoff Goodhill at Washington University in St Louis for an NIH-funded project to help improve early diagnosis of ASD by using cutting-edge tools from machine learning and computational ethology. PROJECT. Motor differences are one of the earliest markers of increased ASD likelihood in infancy. Our goal is to develop broadly-applicable diagnostic tools which combine automated extraction of kinematic features from video data with new machine learning techniques to capture ASD motor function variability. As a first step, we are applying cutting-edge developments in computer vision, machine learning and computational ethology to a rich, longitudinal video dataset of infants being screened for ASD. APPLICANT PROFILE. The ideal applicant would have a strong background in all of ASD, human movement, machine learning and computational ethology. However given the rarity of this combination we are happy to consider candidates with only some of this background, but a strong desire to learn about the other elements. LAB ENVIRONMENT. The Goodhill lab is an interdisciplinary environment of students and postdocs from a diverse array of backgrounds including neuroscience, mathematics, physics and engineering, working together on understanding neural circuit computation, particularly relating to neural development. UNIVERSITY ENVIRONMENT. Washington University in St Louis is ranked in the top 10 institutions globally for Neuroscience and Behavior, and offers an outstanding intellectual environment for research in neuroscience. The Goodhill lab has recently moved into Washington University's new start-of-the-art 600,000 sq ft Neuroscience Research Building (https://neuroscience.wustl.edu/research/neuroscience-building) For more information about St Louis see https://explorestlouis.com. To apply please send a CV and detailed cover letter explaining why you are interested in this position to g.goodhill(a)wustl.edu. Review of applications will continue until the position is filled. Professor Geoffrey J Goodhill Departments of Developmental Biology and Neuroscience Director, Center for Theoretical and Computational Neuroscience (ctcn.wustl.edu) Affiliate appointments: Physics, Biomedical Engineering, Computer Science and Engineering, and Electrical and Systems Engineering Washington University School of Medicine 660 S. Euclid Avenue St. Louis, MO 63110 g.goodhill(a)wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd

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[Courses] Cours en ligne en anglais : Test d'hypothèse à deux échantillons (Online Training and Internship: Two Sample Hypothesis Testing)
by PRANAV NERURKAR 17 Jun '24

17 Jun '24

(Apologies for cross posting) Salutations de l'Institut Utkarsh Minds. Nous sommes heureux d'annoncer que l'Institut Utkarsh Minds organise un programme de stage de deux mois sur Python pour le test d'hypothèses statistiques. 🎯 Dates : du 1er juillet au 31 août 2024 🎯 Intervenants : Experts du monde académique et de l'industrie 🎯 Les participants intéressés sont invités à s'inscrire. Lien d'inscription : https://internships.utkarshminds.com/ 🎯 Frais d'inscription : seulement Rs. 99/- (EUR 2 / USD 2) 🎯 Date limite d'inscription : 25 juin 2024 🎯 Comité d'organisation : Pranav Nerurkar pranav.nerurkar(a)utkarshminds.com +91 9619997797 Nous attendons avec impatience votre participation active. Cordialement, Institut Utkarsh Minds Stage en ligne : Test d'hypothèse à deux échantillonsDescription : Rejoignez notre programme de stage en ligne complet axé sur le test d'hypothèse à deux échantillons, conçu pour les étudiants désireux de se plonger dans le monde de l'analyse statistique et de la programmation. Ce stage offre un mélange unique d'apprentissage théorique et d'application pratique, fournissant aux participants une compréhension solide du test d'hypothèse à l'aide de données réelles. Principales caractéristiques : 1. *Cours vidéo interactifs* : - Apprenez les fondamentaux du test d'hypothèse à deux échantillons grâce à des cours vidéo captivants et informatifs. - Comprenez les concepts clés tels que les hypothèses nulle et alternative, les tests t, les tests z, les valeurs p et les intervalles de confiance. 2. *Travaux pratiques de codage* : - Appliquez les connaissances théoriques acquises lors des cours en réalisant des travaux pratiques de codage dans des langages tels que Python ou R. - Travaillez sur des jeux de données réels pour vous exercer à formuler des hypothèses, à effectuer des tests statistiques et à interpréter les résultats. - Bénéficiez de conseils pas à pas pour écrire et déboguer le code afin d'assurer une analyse précise et efficace. 3. *Applications pratiques* : - Explorez diverses études de cas et exemples illustrant l'application du test d'hypothèse à deux échantillons dans différents domaines tels que la santé, la finance, le marketing, et plus encore. - Participez à des projets imitant des scénarios réels où le test d'hypothèse est crucial pour la prise de décision. 4. *Mentorat et soutien* : - Recevez un mentorat de la part de statisticiens et de data scientists expérimentés. - Participez à des sessions de questions-réponses et à des forums de discussion pour clarifier vos doutes et enrichir votre expérience d'apprentissage. 5. *Certification* : - Obtenez un certificat à l'issue de ce stage, attestant de vos compétences et connaissances en test d'hypothèse à deux échantillons. - Ajoutez cette précieuse compétence à votre CV ou à votre profil LinkedIn pour renforcer vos perspectives de carrière. Exigences : - Compréhension de base des statistiques et de la programmation. - Un ordinateur avec accès à internet. - Volonté d'apprendre et d'appliquer de nouveaux concepts. Durée : - Le stage est auto-rythmé et peut être complété en 4 à 6 semaines, en fonction de votre emploi du temps et de votre rythme d'apprentissage. Greetings from Utkarsh Minds Institute! We are excited about the opportunity to help you enhance your skills in this critical area and want to ensure you don't miss out on this valuable experience. 🎯 *Program Dates:* 1st July to 31st August 2024 🎯 *Resource Persons:* Experts from Academia and Industry 🎯 *Registration Fees:* Rs. 99/- only To complete your enrollment, please visit the following link and finalize your registration: https://internships.utkarshminds.com/ *Why Should You Enroll?* - *Comprehensive Curriculum:* Learn practical and theoretical aspects of Python for statistical hypothesis testing. - *Expert Guidance:* Get trained by professionals with extensive experience in the field. - *Affordable Fees:* Gain valuable skills for just Rs. 99. - *Career Advancement:* Enhance your resume and improve your job prospects. The last date for registration is 25th June 2024. Don't miss this chance to advance your skills and career prospects. If you have any questions or need assistance with the registration process, please feel free to reach out to us. *Contact Details:* Pranav Nerurkar Email: pranav.nerurkar(a)utkarshminds.com Phone: +919619997797 Online Internship: Two Sample Hypothesis TestingDescription: Join our comprehensive online internship program focusing on Two Sample Hypothesis Testing, designed for students eager to delve into the world of statistical analysis and coding. This internship offers a unique blend of theoretical learning and practical application, providing participants with a robust understanding of hypothesis testing using real-world data. Key Features: 1. *Interactive Video Lectures*: - Learn the fundamentals of Two Sample Hypothesis Testing through engaging and informative video lectures. - Understand key concepts such as null and alternative hypotheses, t-tests, z-tests, p-values, and confidence intervals. 2. *Hands-On Coding Assignments*: - Apply the theoretical knowledge gained from the lectures by completing coding assignments in languages such as Python or R. - Work on real datasets to practice setting up hypotheses, running statistical tests, and interpreting results. - Get step-by-step guidance on writing and debugging code to ensure accurate and efficient analysis. 3. *Practical Applications*: - Explore various case studies and examples that illustrate the application of Two Sample Hypothesis Testing in different fields such as healthcare, finance, marketing, and more. - Engage in projects that mimic real-life scenarios where hypothesis testing is crucial for decision-making. 4. *Mentorship and Support*: - Receive mentorship from experienced statisticians and data scientists. - Participate in Q&A sessions and discussion forums to clarify doubts and enhance your learning experience. 5. *Certification*: - Earn a certificate upon successful completion of the internship, showcasing your skills and knowledge in Two Sample Hypothesis Testing. - Add this valuable credential to your resume or LinkedIn profile to boost your career prospects. Requirements: - Basic understanding of statistics and programming. - A computer with internet access. - Willingness to learn and apply new concepts. Duration: - The internship is self-paced and can be completed within 4-6 weeks, depending on your schedule and pace of learning. *Pranav A. NERURKAR* Specialist - AI & Data science UTKARSH MINDS +91 961-999-77-97 pranav.nerurkar@ <amandine.deplantes(a)igonogo.io>utkarshminds.com www.utkarshminds.com Nirmala Sadan, Jaya Nagar, Kasturba cross road no. 1, Mumbai - 400066

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Job posts at the Cognitive Science Center at Jagiellonian University
by Marcin 17 Jun '24

17 Jun '24

*Postdoc and PhD Student positions to study neural mechanisms of cognition in naturalistic situations* *Jagiellonian University, Kraków, Poland* *Job Description:* The Jagiellonian University in Kraków, Poland, is excited to announce several upcoming job openings at different levels (postdocs and PhD) to work on the psychophysics and electrophysiology of cognition. These positions are funded by the National Science Center, Poland. We are seeking highly motivated candidates eager to investigate cognition using eye tracking, virtual reality (VR), electrophysiology, psychophysics, and advanced signal processing tools. Interested applicants should contact Marcin Leszczyński to discuss possibilities. *Lab Description:* Successful candidates will join a dynamic research group at the Cognitive Science Center at Jagiellonian University, located in the beautiful city of Kraków. Our lab employs a variety of technologies, including electrophysiology, eye-tracking, VR, and psychophysics, combined with advanced signal processing and machine learning, to study cognition in health and disease. We offer a vibrant international research environment, with English as the working language (no need to speak Polish). We encourage interested candidates to get in touch to discuss the opportunities available. The department provides excellent infrastructure, including supporting staff and state-of-the-art equipment for conducting experiments (e.g., behavioral laboratories, EEG, fMRI, TMS, eye-tracking, and VR setups). Additionally, motivated candidates will have the chance to participate in numerous collaborative projects with partners at Columbia University in New York City, Nathan Kline Institute, and University Hospital in Bonn. *Requirements:* *Postdoc Applicants:* - Must hold, or expect to hold, a doctorate in Psychology, Neuroscience, Computer Science, or related disciplines. - Ideal candidates will have experience designing, performing, analyzing, and disseminating psychophysics studies or experimental studies using eye tracking, VR, EEG, MEG, or LFPs. - Motivated candidates with other relevant experience are also encouraged to apply. - Salary for this position is approximately 9600 PLN per month. *PhD Applicants:* - Should have previous programming experience and a research interest in neuroscience, perception, attention, memory, eye movements, sensory-motor, or multi-sensory interactions. - Previous experience in analyzing psychophysiological signals is an asset. - Ability to work independently and proficiency in English are essential (no need to speak Polish). For further inquiries about the positions, please contact Marcin Leszczyński at marcin.leszczynski(a)uj.edu.pl. *Application Process:* Interested candidates should send the following: - A cover letter describing research interests and motivation to join our lab (max. 2 pages). - Curriculum vitae. - Contact information for two references. Applications will be reviewed on a rolling basis until the positions are filled.

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PsychoPy Course for Cognitive and Social Neuroscience
by elham afshari 17 Jun '24

17 Jun '24

Dear Members, I am happy to announce the launch of a course, designed specifically for cognitive science beginners. If you're new to psychology or neuroscience and want to run experiments with PsychoPy, this course might be useful. Enroll the course here: Mastering PsychoPy for Psychology and Neuroscience <https://www.udemy.com/course/mastering-psychopy-for-psychology-and-neurosci…> This course provids a clear understanding of experimental design using PsychoPy, even for beginners,and has a hands-on approach to experiment building. I thought you might be interested in checking it out, especially if you're looking to enhance your skills in experimental design and implementation. Bests,

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World wide VVTNS series: Wednesday, June 19 at 11am (EDT), Yasaman Bahri , Google DeepMind | Learning and prediction in artificial deep neural networks: scaling, data manifolds, and universality
by David Hansel 16 Jun '24

16 Jun '24

[image: VVTNS.png] https://www.wwtns.online - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture given by Yasaman Bahri Google DeepMind on the topic of Learning and prediction in artificial deep neural networks: scaling, data manifolds, and universality The lecture will be held on zoom on *Wednesday* *June 19, 2024*, at *11:00 am EDT * To receive the link: https://www.wwtns.online/register-page *Abstract: *Developing scientifically-grounded theories for representation learning and generalization in artificial deep neural networks remains a grand challenge of fundamental interest to theoretical neuroscience and machine learning. I will discuss our work on one facet of this challenge — namely understanding generalization or “scaling laws” in learned neural networks as a function of basic control variables. I’ll discuss a taxonomy we develop that classifies different regimes of scaling behavior. We identify regimes where generalization exhibits universal scaling behavior and others where it can be traced back to properties of the data and neural architecture. The theoretical analysis is enabled by leveraging exactly solvable models of deep neural networks that arise naturally in the limit of large hidden layers. Along the way, I’ll also discuss our work on these theoretical models, which have been a useful starting point for theoretical descriptions of neural network dynamics. Finally, I’ll discuss our findings connecting generalization in neural networks to properties of the learned data manifold. I’ll close by discussing future directions and new hypotheses that emerge from our findings *About VVTNS : Created as the World Wide Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), its aim is to be a platform to exchange ideas among theoreticians. Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars, **held on Wednesdays at 11 am ET,** are 45-50 min long followed by a discussion. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ ᐧ ᐧ ᐧ ᐧ

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2024 SPARC FAIR Codeathon: apply now and choose a project
by Elisabetta Iavarone 14 Jun '24

14 Jun '24

Dear all, The Common Fund SPARC program, with funding from the National Institutes of Health (NIH), has a three-day in-the-cloud Codeathon that may be of interest for the comp-neuro community. The fourth annual virtual SPARC Codeathon will take place *online **August 10-12*. This global prize competition is currently recruiting participants to make SPARC data and resources <https://sparc.science/> more Findable, Interoperable, Accessible, and Reusable (FAIR). Any interested participant can join projects spanning data visualization, simulation tool development, python workflow creation, and more to compete for $50,000 in prizes. Follow this link to learn more and sign up today! https://sparc.science/news-and-events/events/2024-sparc-fair-codeathon Elisabetta Iavarone, On behalf of the SPARC FAIR Codeathon team

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Open position at Goettingen University - PhD student (f/m/d) - SPP 2205
by von Behren, Christina 14 Jun '24

14 Jun '24

The Department of Data-driven Analysis of Biological Networks at the Georg-August-Universität of Göttingen invites applications for a position as PhD student (f/m/d)<https://www.uni-goettingen.de/de/644546.html?details=2851/> This position is available starting from November 1st, 2024. It is a part time position with a limited contract of 3 years. Salary and working hours will be according to the German grade 13 TV-L (65%, currently 25,87 hours per week). The position will be associated with the group of Prof. Dr. Michael Wibral, Göttingen Campus Institute for Dynamics of Biological Networks (CIDBN)<https://www.uni-goettingen.de/de/608362.html/>. We are recruiting a PhD student for the interdisciplinary research project "Evolutionary Convergence of Hierarchical Information Processing" funded by the German Research Foundation (DFG) within the research initiative SPP2205 "Evolutionary optimization of neuronal processing<https://www.uni-goettingen.de/de/618311.html>. The project aims to establish the common information theoretic principles of computation in hierarchical neural systems that are conserved across species (in particular mammals and birds). Specifically, we will use the analysis of information theoretic timescales [1], the correlation of information storage and transfer [2] and the analysis of unique, redundant and synergistic information [3,4] in order to take a comparative approach to neural computation in the primate and the avian brain. The project will be pursued in close collaboration with the research groups of Viola Priesemann at the Max Planck Institute for Dynamics and Self-Organization in Göttingen and Onur Güntürkün, Jonas Rose and Roland Pusch at the Ruhr University of Bochum. We are looking for candidates with an excellent Master degree in physics, neuroscience, cognitive science, computer science or a related field who are committed to pursuing a career in research. The successful applicant will develop novel information theoretic models and measures of neural computation and apply them to electrophysiological recordings to analyze predictive hierarchical information processing in the primate and the avian brain. The ideal candidate should possess exceptional analytical skills, coupled with a proficiency in coding in a language that is pertinent to data analysis. We offer the opportunity to become a member of a vibrant community dedicated to innovative research and teaching at the frontier of the exact and biological sciences, and to connect to the latest developments in information theory, in particular partial information decomposition. The Göttingen Campus is a leading center of biophysics and neuroscience in Europe hosting numerous internationally renowned research institutions, including the University and its Medical Center, the three Max Planck Institutes in the Life Sciences, the European Neuroscience Institute, the German Primate Center, and the Bernstein Center for Computational Neuroscience (BCCN) Göttingen. The University of Göttingen is an equal opportunities employer and places particular emphasis on fostering career opportunities for women. Qualified women are therefore strongly encouraged to apply in fields in which they are underrepresented. The university has committed itself to being a family-friendly institution and supports their employees in balancing work and family life. The university is particularly committed to the professional participation of severely disabled employees and therefore welcomes applications from severely disabled persons. In the case of equal qualifications, preference is given to applications from people with severe disabilities. A disability or equality is to be included in the application in order to protect the interests. Please submit your application in digital form only and send all relevant documents in one single PDF-document, including a letter of interest, your curriculum vitae with a list of publications, copies of your certificates and contact information of at least two references to Wibral_lab(a)uni-goettingen.de by August 1st, 2024. If you have any questions, please contact Prof. Dr. Michael Wibral via E-Mail: michael.wibral(a)uni-goettingen.de Please note: With submission of your application, you accept the processing of your applicant data in terms of data-protection law. Further information on the legal basis and data usage is provided in the Hinweisblatt zur Datenschutzgrundverordnung (DSGVO) https://www.uni-goettingen.de/hinweisdsgvo [1] Rudelt et al. (2021) Embedding optimization reveals long-lasting history dependence in neural spiking activity. PLoS Comp Biol 17(6):e1008927 [2] Wollstadt et al. (2023) Information-theoretic analyses of neural data to minimize the effect of researchers' assumptions in predictive coding studies. PLOS Comp Biol 19 (11) e1011567 [3] Gutknecht et al. (2021) Bits and pieces: Understanding information decomposition from part-whole relationships and formal logic. Proc. Royal Soc. A 477 (2251), 20210110 [4] Ehrlich et al. (2023) A measure of the complexity of neural representations based on partial information decomposition, Transactions on Machine Learning Research 5 ------ Goettingen Campus Institute for Dynamics of Biological Networks Bernstein Center for Computational Neuroscience Goettingen University of Goettingen Heinrich-Dueker-Weg 12 37073 Goettingen Germany

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11th rTAIM Online Seminar | Walter Sinnott-Armstrong (Duke Uni.) | 26 June 2024 - 3pm Lisbon Time Zone | Zoom
by steven gouveia 13 Jun '24

13 Jun '24

Dear All, Following the 10th rTAIM Online Seminar (available here: https://www.youtube.com/watch?v=ZsRMi76gv9c) we are happy to announce the 11th rTAIM Online Seminar with the participation of Professor Walter Sinnott-Armstrong (Duke University, USA), on the 26th June 2024, 15h-16h30 Lisbon Time Zone, via Zoom. Title: The Moral AI and How We Get There Abstract: Artificial intelligence (AI) is beginning to be used for many life-changing decisions in medicine. Critics object that using AI in these areas is too likely to lead to harm, unfairness, and other moral wrongs. In response, I will argue that these decisions can be made safer and more ethical by building human moral values into the AI decisionmaker. But how can we do that? I will discuss problems for some proposed ways to build morality into AI from the top down and from the bottom up. Then I will explain our lab’s novel hybrid alternative, which surveys human moral judgments and then corrects for ignorance, confusion, and partiality. Because our approach is based on idealized observer theories in ethics, it minimizes substantive assumptions about what is morally right or wrong, and it can be used in a wide variety of contexts. I will report initial empirical results using our method and discuss potential applications to kidney allocation and dementia. Short bio: Walter Sinnott-Armstrong is Chauncey Stillman Professor of Practical Ethics in the Department of Philosophy and the Kenan Institute for Ethics at Duke University. His most recent book is Moral AI and How We Can Get There, with Jana Schaich Borg and Vincent Conitzer in 2024. Zoom: Link: https://videoconf-colibri.zoom.us/j/98415196784?pwd=a3dHbmF4VzlTaVczWTB6QzV… Meeting ID: 984 1519 6784 Passcode: 765321 More info: https://trustaimedicine.weebly.com/<https://trustaimedicine.weebly.com/rtaim-seminars.html>rtaim<https://trustaimedicine.weebly.com/rtaim-seminars.html>-seminars.html<https://trustaimedicine.weebly.com/rtaim-seminars.html> We are also happy to announce that the Call for Abstract for the 3rd International Conference on the Ethics of Artificial Intelligence that will happen in the São Miguel Islands in the Azores (Portugal), between 19-25 September 2024 (online and in-person), is OPEN for submissions (notifications of acceptance/rejectance) are given in 7-10 days). You can find the information related to the 3ICEAI here: https://trustaimedicine.weebly.com/3iceai.html Sincerely, Organizer

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