- Comp-neuro - lists.cnsorg.org

Postdoc opening in analysis of complex hippocampal oscillations (Demian Battaglia and Romain Goutagny's FunSy team, Strasbourg)
by BATTAGLIA Demian Dec. 20, 2022

Dec. 20, 2022

We are currently inviting applications for a full-time postdoc position under the joint co-mentoring of Dr. Demian Battaglia and Dr. Romain Goutagny (University of Strasbourg, France; Functional System's Dynamics team – FunSy, https://funsyteam.org<https://funsyteam.org/>). The position starts as soon as possible and can last up to two years. This job offer is funded by the French ANR "HippoComp" project, which focuses on the complexity of hippocampal oscillations and the hypothesis that such complexity can serve as computational resource. In our joint FunSy team, we perform electrophysiological recordings in hippocampus and cortex during spatial navigation and memory tasks in mice (wild type and mutant developing various neuropathologies) and have access to vast data through local and international cooperation. Furthermore, we use a large spectrum of computational tools ranging from time-series and network analyses, information theory and machine-learning to multi-scale computational modeling. A good idea about some of the approaches used in the lab can be found in this recent preprint: Douchamps et al. 2022. Hippocampal gamma oscillations form complex ensembles modulated by behavior and learning, bioRxiv (https://doi.org/10.1101/2022.10.17.512498) We are seeking for various profiles of candidates, with main expertise in either computational or experimental neuroscience. Computational project components would deal with numerically-intensive data analyses (dimensional reduction, encoding/decoding, design of discriminative features...). Experimental project components would focus primarily on simultaneous fiber photometry and local-fields potentials recordings, together with the pre-processing of these data. Interested candidates could have hybrid experimental/computational projects. The ideal candidate will have a doctorate in systems or computational neuroscience, with previous experience in the analysis of rich datasets. In addition, we expect programming skills (e.g., Python, C/C++, Matlab), good communication skills in English (oral and written), the ability to work well in an international team, curiosity and open-mindedness. Strasbourg University is home of an emergent and active community in neuroscience, from molecules and cells to whole brain imaging and behavior, in relation with clinics. The proximity with Germany and Switzerland is an asset allowing interactions with transnational Computational and Neuroscience teams. Strasbourg, home of important European institutions, is a small fascinating city with a rich student and cultural life, well connected via high-speed train to important European cities (e.g. less than two hours from Paris). DEADLINE FOR APPLICATION: January 15th 2023 Please send your application, including CV, motivation letter and representative publications (preprints accepted) electronically, to both PIs (Romain Goutagny and Demian Battaglia). In addition, contacts of at least two academic references must be communicated (contact email or recommendation letter attachments). Pre-selected candidates will be interviewed over Zoom or invited to give a talk if possible. We are committed to equal opportunity hiring. We strongly encourage applications from qualified women or candidates from any country. Contact persons: Demian Battaglia, dbattaglia AT unistra.fr<mailto:dbattaglia@unistra.fr> Romain Goutagny, goutagny AT unistra.fr<mailto:goutagny@unistra.fr>

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New Book: Introducing Computation to Neuroscience – Selected Papers of George Gerstein
by Dr. David Goyer Dec. 20, 2022

Dec. 20, 2022

Prof. Sonja Grün (INM-6, INM-10 & IAS-6; Jülich Research Center), together with colleagues Profs. A. Aertsen, P.E. Maldonado and G. Palm, recently published the book “Introducing Computation to Neuroscience – Selected Papers of George Gerstein <https://link.springer.com/book/10.1007/978-3-030-87447-6>”. George Gersteinhad his roots in physics and was known for his long-term commitmentto transformingneuroscience intoa field ofmore rigorous science, like physics was at the time. With this, hewas miles ahead of the ﬁeld, consistently striving for quantitative analyses, mechanistic models, and conceptual clarity. Eventually, he pioneeredwhat we now know asComputational Neuroscience-many years before the term was coined. But the overarching goal of George Gerstein’s research was always to understand the functional organization of neuronal networks in the brain. Prof. Grün and the editors nowhave compiled a selection of George Gerstein’s many seminalexperimental, theoretical andcomputational contributions to neuroscience into a single, comprehensive volume. They also provide a fresh view on the subjects of his work, as several of George Gerstein’s former students and collaborators kindly contributed introductionsto various chapters.This does not onlyframethe papers in their historical and present context, it alsoaddsthepersonal touch of their involvement in generating the papersand gives a glimpse into lab life. The book itselfis organized intoa series of chapters with differentsubjects, each one containing reprintsof George Gerstein’s papersin chronological order. Thereby, each of these chapters traces the developmentof George Gerstein’s seminal contributions to the Neurosciences, be it in the domain of neuron and network modeling or in the area of neuronal data analysis techniques. In the words of the editors: "/We hope that, taken together, these various Chapters and their Introductions will help the reader appreciate how much our current thinking on brain function owes to George Gerstein’s research and the insights gained from it. George was not only an innovative thinker in theory, experiment and analysis methodology, he also inspired by his mode of thinking science. Thus, in a way, this book is both a product of this inspiration and a tribute to it./" -- Dr. David Goyer Scientific Coordinator Institute of Neuroscience and Medicine (INM-6) Computational and Systems Neuroscience & Institute for Advanced Simulation (IAS-6) Theoretical Neuroscience Jülich Research Centre and JARA Jülich Germany phone: +49-1756402993

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[Jobs] 2 Year independent Postdoc at the Institute for Neural Computation, Bochum, Germany
by Laurenz Wiskott Dec. 19, 2022

Dec. 19, 2022

The Institute for Neural Computation of the Faculty for Informatics is looking for a postdoc (m,f,x) in the field of Computational Neuroscience for 2 years, 39,83 hours per week, E13 TVL The Institute for Neural Computation is part of the Faculty of Computer Science at the Ruhr-University Bochum, see https://www.ini.rub.de/. It focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. There is an open position for a postdoc in the group „Theory of Neural Systems“ of Prof. Dr. Laurenz Wiskott to be filled as soon as possible. The position is planned for two years with salary level 100% TV-L E13, the standard German salary for postdocs. This position offers the opportunity to develop your own research profile and establish an independent research group. The research topic should be in the field of computational neuroscience on a system level, in particular modeling the visual system, episodic memory, or navigation in mammals. Collaborations with colleagues at the institute are welcome. extent: full-time duration: temporary beginning: as soon as possible application deadline: 21.11.2022 Your tasks: Independent research projects and publications. Acquiring third party funding. Teaching. A lot of room for own ideas and initiatives. Supervising student projects and your own PhD projects. Active participation in the local research environment. Your profile: Active participation in the local research environment. Solid knowledge in Computational Neuroscience. Potential to develop an original independent research agenda in one of the above-mentioned topics. Our offerings: An interesting interdisciplinary environment in the field of experimental and computational neuroscience / machine Learning. Opportunity to develop an independent research profile and your own research group. Opportunity to pursue further scientific qualification. A lot of room for own ideas and initiatives. Additional information: At the request of the applicant (m,f,x), the staff council may be involved in selection interviews. The load of teaching will be calculated according to § 3 of Lehrverpflichtungsverordnung (state of North Rhine-Westphalia). The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is RUB’s declared aim. The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome. Contact details for your application: Prof. Dr. Laurenz Wiskott, Phone: +49234 32 27997 Travel expenses for interviews cannot be refunded. For information on the collection of personal data in the application process see: https://www.ruhr-uni-bochum.de/en/information-collection-personal-data-appl…. ANR: 1267 until 2023-01-02 Applications (CV, transcript of records for PhD, MSc and BSc, statement of purpose) should be sent as a single pdf file to laurenz.wiskott(a)rub.de. Official job announcement: https://jobs.ruhr-uni-bochum.de/jobposting/360e82936d27d5749b276888153c2cb1…

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Post-doc position with Friedemann Zenke at the FMI, Switzerland
by Friedemann Zenke Dec. 19, 2022

Dec. 19, 2022

The Computational Neuroscience Group, led by Friedemann Zenke at the Friedrich Miescher Institute in Basel, Switzerland (www.fmi.ch) is looking for a post-doctoral researcher. Position available from the beginning of 2023 (or later). Topics of interest include • Learning algorithms (bio-inspired self-supervised learning and credit assignment) • Spiking neural networks (sparsity, neuronal complexity, efficient training) • Continual learning (synaptic consolidation and circuit mechanisms) • Neuromorphic computing (online learning and dynamic neural networks) • Information representation in biological and artificial neural networks See www.zenkelab.org for more information. The position • Conduct research in computational neuroscience and bio-inspired machine intelligence. • Write research articles and present them at international conferences. • Publish in neuroscience journals and machine learning venues such as ICML, NeurIPS, ICLR, etc. • Interact and collaborate with experimental neuroscience groups or neuromorphic hardware developers nationally and internationally. Ideal profile • You are passionate about neural networks and enjoy tackling difficult research questions. • You hold a Ph.D. from a related discipline and are a team player. • You have published and possess solid analytical and programming skills. • Fluency in English, both spoken and written, is required. We offer • A diverse international work environment with room to develop one's project. • The option to collaborate with leading experimental groups in circuit neuroscience. • A vibrant lab environment with the possibility to acquire supervision experience if desired. • Opportunities to travel to international conferences or summer schools. • Competitive salary, professional career development, benefits, and working conditions. For more details, see https://www.fmi.ch/education-careers/postdoc-activities/. Application If interested, please get in touch with friedemann.zenke(a)fmi.ch. Please include: • CV (including publication list) • A brief statement of research interest • Contact details of two to three references -- www.zenkelab.org

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World's first Master of Neuromorphic Engineering courses
by Bharath Ramesh Dec. 19, 2022

Dec. 19, 2022

Dear Engineers, scientists and computational neuroscience enthusiasts, The International Centre for Neuromorphic Systems, Western Sydney University, invites both domestic and international students to apply for the world’s first Master of Neuromorphic Engineering courses. We offer several programs, including a Graduate Certificate, a Graduate Diploma, a 1.5-year industry-oriented degree and a two-year research-oriented Master’s course in Neuromorphic Engineering. We seek dedicated, curious and open-minded scientists, engineers, physicists, electronics tinkerers, hardware and software hackers, and roboticists from diverse backgrounds. The course builds on the research background of our Neuromorphic Engineering and Event-Based Processing research staff. Successful applicants will receive significant mentorship. Mentors and course instructors will equip students with special digital vision and audition processing capabilities which are rarely taught at other Universities in the world. Mentors and instructors will provide students with opportunities to apply skills learned to practical projects which align with industry need. Although the post graduate courses will equip graduates with many in-demand machine-learning techniques, Neuromorphic Engineering researchers go beyond status-quo Machine Learning so that they can find solutions to issues that block progress in AI machine learning sensing and computer vision. Neuromorphic Engineering seeks to progress beyond failures in regular machine learning approaches as conventional approaches usually fail to generalise, are not environmentally sustainable, and are poorly suited to high-stakes time-critical low-powered applications. Currently demonstrated applications of Neuromorphic Engineering range from space tracking, intelligent sensing, online learning, one-shot learning, computer vision, computer listening, anomaly detection, remote sensing, lightning characterisation, surveillance applications, biological modelling and medicine. The course is currently accepting applications for 2023 entry. If you are considering any of these courses, we recommend applying now. The application deadline is February 2023. For more information about the course, please visit: Master of Applied Neuromorphic Engineering | Western Sydney University<https://www.westernsydney.edu.au/future/study/courses/postgraduate/master-o…> https://student-westernsydney.studylink.com/index.cfm?event=security.showLo… HOW TO APPLY: Submitting an online application is easy and free for Australian and New Zealand students. Applications for students we sincerely welcome applications outside of Australia and these external applications require a small processing fee. Successful applicants will be eligible for an Australian student VISA. Simply click on THIS LINK<Postgraduate students | Western Sydney University<https://www.westernsydney.edu.au/future/study/how-to-apply/postgraduate-stu…>> and follow the instructions. Western Sydney has a five-star ranking in 5-star ranking in: Teaching, Employability, Internationalisation, Facilities, Innovation, Inclusiveness Western Sydney is Ranked 1st in the world for commitment to the U.N. Sustainable Development Goals (SDGs). Furthermore, it is ranked 3rd in the world for SDG 5: Gender Equality and 4th in the world for SDG 10: Reducing Inequalities. See this link for more information: https://www.westernsydney.edu.au/future/why-western/global-rankings#overall<https://www.westernsydney.edu.au/future/why-western/global-rankings%23overa…> For any questions, please do not hesitate to get in touch. Bharath Ramesh, PhD b.ramesh(a)westernsydney.edu.au

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Error forward propagation: Feedforward Closedloop Learning (FCL)
by Bernd Porr Dec. 18, 2022

Dec. 18, 2022

Dear all, There has been a lot of interest recently in performing deep learning without backprop - papers by Geoff Hinton and Barak Pearlmutter in particular showing how supervised and self-supervised learning can be achieved solely with forward message propagation. We wanted to mention here our own work dating back to 2019, in which we realised real-time reinforcement learning in a closed-loop setting via the forward propagation of error signals. Naturally forward propagation has the attraction of biological feasibility, but from our point of view the more important point is that error signals are then defined in the space of sensory inputs rather than motor outputs, which makes a lot more sense in the context of a self-contained autonomous agent. Rather than the reward functions of Q learning, we use reflex circuits to generate the errors: the goal of sensory learning is to predict disturbances before they occur, thereby silencing the reflex. To see the system in operation, here is a real robot learning a simple line-following task, where the system initially uses a light sensor to drive a reflex steering action, and learning discovers predictive information from vision which pre-empts this reflex: https://sigmoid.social/@berndporr/109534507823054808 Because the algorithm works for deep networks, arbitrarily complex predictive cues can in principle be discovered. Source code and paper: https://github.com/glasgowneuro/feedforward_closedloop_learning We would be highly interested to hear views on this approach. /Bernd Porr and Paul Miller -- http://www.berndporr.me.uk http://www.attys.tech +44 (0)7840 340069

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Sixth Groningen Spring School on Cognitive Modeling
by Thomas Dec. 16, 2022

Dec. 16, 2022

____________________ Sixth Groningen Spring School on Cognitive Modeling – ACT-R, Nengo, PRIMs – Date: 27-31 March 2023 Location: Groningen, the Netherlands Fee: € 305 (late fee after February 26 will be € 355) More information and registration: www.cognitive-modeling.com/springschool ____________________ Dear colleagues and students, We are excited to announce the sixth Spring School on Cognitive Modeling in Groningen, from 27-31 March 2023! This time, the Spring School will cover three different modeling paradigms: ACT-R, Nengo, and PRIMs. Each of these topics consists of a series of lectures, as well as a number of hands-on exercises (tutorials). Past years have shown that students get most out of the spring school if they really emerge themselves into one modeling paradigm. We therefore recommend you choose one topic for which you will attend both the lectures as well as the tutorials. In addition, you can select a second paradigm, for which you attend the lectures only. To give students a broader picture, there will also be three guest lectures throughout the week. These lectures each give an introduction to yet another modeling paradigm: accumulator models (Leendert van Maanen), error-driven learning models (Jacolien van Rij), and dynamical systems (Herbert Jäger). Everyone is encouraged to attend those lectures. To round of the program, there will be a poster session, where students present themselves and their research, as well as a city tour, and our (in)famous spring school dinner. Registration is now open. Please feel free to forward the information to anyone who might be interested in the Spring School. We are looking forward to welcoming you (again) in Groningen, The Spring School team springschool(a)rug.nl ______________ ACT-R Teachers: Jelmer Borst, Stephen Jones, & Katja Mehlhorn (University of Groningen) Website: http://act-r.psy.cmu.edu ACT-R is a high-level cognitive theory and simulation system for developing cognitive models for tasks that vary from simple reaction time experiments to driving a car, learning algebra, and air traffic control. ACT-R can be used to develop process models of a task at a symbolic level. Participants will follow a compressed five-day version of the traditional summer school curriculum. We will also cover the connection between ACT-R and fMRI. Nengo Teacher: Terry Stewart and Andreas Stöckel (University of Waterloo) Website: http://www.nengo.ca Nengo is a toolkit for converting high-level cognitive theories into low-level spiking neuron implementations. In this way, aspects of model performance such as response accuracy and reaction times emerge as a consequence of neural parameters such as the neurotransmitter time constants. It has been used to model adaptive motor control, visual attention, serial list memory, reinforcement learning, Tower of Hanoi, and fluid intelligence. Participants will learn to construct these kinds of models, starting with generic tasks like representing values and positions, and ending with full production-like systems. There will also be special emphasis on extracting various forms of data out of a model, such that it can be compared to experimental data. PRIMs Teacher: Niels Taatgen (University of Groningen) Website: https://www.ai.rug.nl/~niels/prims/index.html How do people handle and prioritize multiple tasks? How can we learn something in the context of one task, and partially benefit from it in another task? The goal of PRIMs is to cross the artificial boundary that most cognitive architectures have imposed on themselves by studying single tasks. It has mechanisms to model transfer of cognitive skills, and the competition between multiple goals. In the tutorial we will look at how PRIMs can model phenomena of cognitive transfer and cognitive training, and how multiple goals compete for priority in models of distraction. ______________ — Thomas Tiotto, PhD Candidate, CogniGron - Groningen Cognitive Systems and Materials University of Groningen Nijenborgh 9, 9747 AG Groningen, The Netherlands Email: t.f.tiotto(a)rug.nl Profile: https://www.rug.nl/staff/t.f.tiotto/ Office: 5161 0318 Sent with Spark

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Call for Papers - IEEE T-MBMC - Special Issue on Bio-Chem-ICTs
by Murat Kuşcu Dec. 15, 2022

Dec. 15, 2022

IEEE Transactions on Molecular, Biological and Multi-Scale Communications Special Issue on Bio-Chem-ICTs: Synergies between Bio/Nanotechnologies and Molecular Communications https://www.comsoc.org/publications/journals/ieee-tmbmc/cfp/bio-chem-icts-s… ----------------------- CALL FOR PAPERS Molecular Communications (MC) is a fundamental means of information exchange ubiquitously observed in nature. It has recently attracted the attention of researchers who have been working in information and communication technologies (ICT) and striving to create cooperative ‘nanonetworks’ of artificial nanomachines, which can be interfaced with or immersed in natural biological systems. Application of ICT tools to this natural modality of communications has laid the foundations of bio-inspired, engineered MC systems, and also contributed to the understanding of natural MC networks. It is no wonder that such fundamental form of communications has been a topic of significant interest in many diverse research fields beyond ICT, such as synthetic biology, systems chemistry, micro/nanorobotics, network medicine, biophysics and physiology, biochemical sensing, lab- and organ-on-chips, bio-interfaces, molecular and biological computing, drug discovery, design and delivery. However, different languages are typically adopted by different fields to refer to the same phenomenon that the ICT researchers call molecular communications, such as chemical communications, biological/cell signaling, interaction networks, which all fundamentally denote information transfer via mass transport and/or biochemical reactions and interactions. Despite the significant overlap in the problem and the application domain, not only the language but also the research methodologies and the solution approaches are diverse, partly due to the apparent lack of strong links between different research communities. On the other hand, closer interactions between these disciplines can create important synergies that can help collaboratively target more challenging research problems and develop unprecedented applications, where the power of true interdisciplinarity is unleashed. These interactions can also help better identify the common motifs in the heterogeneous sea of molecular communication problems and scenarios comprising both biotic and abiotic systems, and help reframe and standardize the way we approach biological and bio-inspired communications in the hope of enabling a common scientific and engineering language. The aim of this Special Issue is to facilitate such interactions by bringing together the contributions of prominent researchers from diverse fields that share a common denominator with the ICT approach to MC. Reflecting different perspectives on natural and engineered molecular communications, and appreciating the diversity of approaches and methodologies, the Special Issue will ultimately help identify the potential interaction pathways between different research areas and communities, that can lead to fruitful collaborations and synergy. To this end, we solicit original contributions (technical or position/survey/tutorial/perspective articles) on a very diverse set of topics including but not limited to: ** Molecular communication among synthetic cells, and between synthetic and natural cells ** Molecular communication among nanoparticles, and between nanoparticles and natural/synthetic cells ** Collective micro/nanorobotic swarms and active matter based on molecular communications ** Physical limits to communication, sensing, and information processing in natural and synthetic bio/nano systems ** Network medicine, communication and network biomarkers of diseases ** Engineering of protein-protein and other molecular interactions, de novo design of proteins and artificial receptors for sensing and molecular communications ** Semantic information in biological networks ** Bio-interfaces (e.g., neural interfaces) relying on molecular interactions, redox reactions, and ionic carriers ** New sensing techniques and chemical & biosensor architectures targeting dynamic bio/chemical signals ** New nanomaterials and device architectures for bio-nano interfaces, and micro/nanomachines & molecular machines capable of molecular communications ** Drug design techniques exploiting molecular interactions, network-based approaches to drug discovery ** Smart drug delivery systems and techniques ** Biological and molecular computing ** Signaling aspects of lab-on-a-chip, organ-on-a-chip, multi-organ-on-a-chip, body-on-a-chip, disease-on-a-chip applications --------------------------- IMPORTANT DATES Manuscript Submission Deadline: 15 March 2023 First Notification: 30 April 2023 Acceptance Notification: 30 May 2023 Final Manuscript Due: 30 June 2023 Publication Date: September 2023 --------------------------- GUEST EDITORS Murat Kuscu Department of Electrical and Electronics Engineering Koc University, Turkey Email: mkuscu(a)ku.edu.tr Pasquale Stano Department of Biological and Environmental Sciences and Technologies University of Salento, Italy Email: pasquale.stano(a)unisalento.it Gregory F. Payne Institute for Bioscience and Biotechnology Research University of Maryland, USA Email: gpayne(a)umd.edu Bige D. Unluturk School of Computer Science and Electronic Engineering Michigan State University, USA Email: unluturk(a)msu.edu Malcolm Egan University of Lyon, Inria, INSA-Lyon, CITI, France Email: malcolm.egan(a)inria.fr Michael T. Barros School of Computer Science and Electronic Engineering University of Essex, UK Email: m.barros(a)essex.ac.uk --------------------------- SUBMISSION GUIDELINES Prospective authors should submit their manuscripts following the IEEE TMBMC guidelines ( https://www.comsoc.org/publications/journals/ieee-tmbmc/information-for-aut… ). Authors should submit a manuscript through Manuscript Central ( https://mc.manuscriptcentral.com/tmbmc) ---------------------------

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Interdisciplinary PhD program in London, UK
by Silver, Angus Dec. 15, 2022

Dec. 15, 2022

Interdisciplinary PhD program in London, UK – call for 2023 applications – deadline 10th January. The London Interdisciplinary Biosciences Consortium (LIDo) Doctoral Training Partnership (DTP) is a BBSRC funded collaborative partnership offering world-class interdisciplinary research. LIDo unites an exciting team of outstanding universities and unique specialist institutions to provide innovative cutting-edge interdisciplinary research in the heart of one of the world's most vibrant and scientifically stimulating cities. LIDo will be offering 41 fully funded studentships in September 2023 across our DTP and iCASE routes of entry; these include home tuition fees and a tax-free stipend in the region of £19,668. A maximum of 11 of these positions can be offered to students eligible for overseas fee rates, where LIDo will cover the full fee amount. DTP Route In the first year of the programme DTP students will undertake two 4-month research projects in different partner institutions, selecting from a catalogue of over 200 topics. The choice of PhD topic is finalised after the second rotation project. Research opportunities are available across the breadth of BBSRC remit. Exemplar projects can be found on our website: https://www.lido-dtp.ac.uk/projects and DTP students will have the opportunity to contact potential supervisors in the Spring ahead of our call for projects. LIDo is particularly keen to welcome students from mathematics, computer science, engineering and the physical sciences who are eager to apply their skills and experience to biological problems and students from the plant sciences for exciting new projects available at our specialist academic and associate partners. All DTP students undertake a compulsory 3-month internship (PIPS) during their PhD to gain experience and context for careers where the transferable skills developed during their PhD programme can be usefully employed. iCASE Route Industrial collaborative (iCASE) students begin working on their named project from the start of the course. These projects represent genuine partnerships between academics within the LIDo consortium and industrial colleagues, allowing students to experience both distinctive environments in a mutually productive and supportive team and an extended placement of 3-18 months with their non-academic partner. Training and Cohort Building During the first-year, students will receive advanced training in fundamental and advanced mathematical, computational, and statistical skills for interdisciplinary and systems biology research. Expert in-house training in biological concepts and exposure to the history, trends and structure of the biotechnology and pharmaceutical industries make up the remaining first year teaching. Each year a week of cross research council remit teaching cushions the two rotations providing students the opportunity to hear from academic, industry, government, and not-for-profit speakers on a range of topics in the boundaries of BBSRC remit. The extraordinary LIDo teaching and research-intensive environment sits within a framework of robust and established cohort building activities, culminating each year in an academic retreat for the students. Application We enthusiastically invite applications by all highly motivated students from a wide range of academic backgrounds including biological, physical, computational, engineering or mathematical disciplines. Applicants must hold, or be expected to achieve, a first or high upper second-class honours degree (or equivalent), or an MSci or other Masters degree. For details on how to apply and the link to our online application form please go to: www.lido-dtp.ac.uk/apply<http://www.lido-dtp.ac.uk/apply> The application window will close on Tuesday 10th January 2023 at 5pm. R. Angus Silver, FRS Professor of Neuroscience and Wellcome Trust Principal Research Fellow Department of Neuroscience, Physiology and Pharmacology University College London Gower Street London WC1E 6BT Tel : 020 7679 7830 www.ucl.ac.uk/silverlab/

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Associate Research Scholar at Columbia University
by Michael Woodford Dec. 15, 2022

Dec. 15, 2022

*Position for Associate Research Scholar with the Cognitive and Behavioral Economics Initiative, Columbia University* The Cognitive and Behavioral Economics Initiative (CBEI) at Columbia University invites applications for an Associate Research Scholar (ARS) position to begin May 1, 2023 or later. The appointment will initially be for one year but is renewable based on satisfactory performance and availability of funding. The Associate Research Scholar will facilitate research on number cognition and the role of imprecise number representations as a source of errors and biases in economic decisions. A focus of the research will be the comparative evaluation of alternative quantitative models of the resource constraint that limits the precision of number representations, and the way in which these representations change depending on the statistics of the decision problems that are presented and, on the time allowed for mental processing. The Associate Research Scholar will conduct behavioral experiments, develop and test computational models of cognitive processes, and participate in data analysis and manuscript preparation, under the direction of Prof. Michael Woodford. *Qualifications* Applicants must have a Ph.D. in Economics, Neuroscience, Computer Science, Physics, or a related discipline, and at least three years of postdoctoral experience in related research. The ideal candidate will have strong computational skills, and experience conducting behavioral experiments, as well as superior motivation, drive, and demonstrated aptitude for research. Previous experience with interdisciplinary collaboration is strongly desired. For additional details and instructions for how to apply, see the job posting at https://academic.careers.columbia.edu/#!/108222.

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