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SoAIR 2019 [Extended Deadline]: JST-CREST / IEEE-RAS Spring School on "Social and Artificial Intelligence for User-Friendly Robots" in Japan

by Amir Aly

CALL FOR APPLICATIONS **Apologies for cross posting ** We are pleased to call for applications for the *JST-CREST / IEEE-RAS* spring school on: "*Social and Artificial Intelligence for User-Friendly Robots*" * Which will be held from 17-24 March, 2019 in Shonan Village, Japan *after the *Human-Robot Interaction (HRI)* conference that will be held in the near South Korea. *Webpage: **https://inic8.bitbucket.io/SoAIR19/* <https://inic8.bitbucket.io/SoAIR19/> *I. Aim and Scope *Autonomous and intelligent systems are progressively moving into spaces, which have previously been predominantly shaped by human agency. Unlike in the past where machines obediently served their human operators, machines now increasingly act without the intervention of a human. Artificial intelligence is meeting new challenges in the world, though human-like intelligence may still be a distant goal. Robots in factories are coming out of their cages. Autonomous cars are being tested on streets with regular human-driven cars. The private household is changing with the appearance of not only robotic vacuum cleaners, but also with the first-generation of social robots and smart devices. The challenges that face both the robotics and artificial intelligence communities are how the necessary intelligence for such new environments can be created as well as how to make artificial agents capable of not only solving tasks at hand but also considering social environments around them during interaction with human users so as to behave appropriately. Within the school, we plan to address the tension created by the balance between task-specific artificial intelligence and the demands of sociability required to function effectively in human-centered environments. ** *Who should apply?* We invite *Masters and PhD students* as well as *post-doctoral candidates and researchers from industry* with relevant research background to apply for this spring school. *Additional support could be available based on eligibility.* ** *This spring school is a Technical Education Program (TEP) endorsed and supported by JST-CREST / IEEE-RAS*. ** *The school aims at bridging the gap between social and cognitive Human-Robot Interaction (HRI), Artificial Intelligence (AI), and Autonomous Vehicles (AV) through high level talks, tutorials, and hands-on workshops (the program will be announced soon).* *II. Keynote Speakers: * 1. * Takayuki Nagai, *Osaka University, Japan 2. * Jun Tani *– Okinawa Institute of Science and Technology (OIST), Japan 3. *Daniele Magazzeni *– King's College London, UK 4. * Yukie Nagai *– National Institute of Information and Communications Technology (NICT), Japan 5. * Tetsuya Ogata* – Waseda University, Japan 6. *Mohamed Chetouani *– University of Pierre and Marie Curie (UPMC), France 7. *Silvia Rossi* – University of Naples, Italy 8. *Agnieszka Wykowska *– Italian Institute of Technology (IIT), Italy 9. *Tetsunari Inamura *– National Institute of Informatics (NII), Japan 10. *Amit Kumar Pandey *– SoftBank (Aldebaran) Robotics, France 11. *Mehul Bhatt* – Orebro University, Sweden (Tutorial) 12. *Mohsen Kaboli –* Bavarian Motor Works (BMW), Germany (Tutorial) 13. *Francesco Maurelli *– Jacobs University, Germany (Preparing Marie Curie funding proposal) 14. *Atsuko Nakatsuka* – Japan Society for the Promotion of Science (JSPS), Japan (Preparing JSPS funding proposal) *III. Submission * The applications must include the following files (combined into one file). No other documents would be necessary (More information is available on the school's webpage). 1. *Curriculum vitae*: A CV detailing relevant aspects of the candidate's academic career that demonstrates her/his relevance to the school theme. Please consider including the list of publications. 2. *Research abstract*: A 200-word research abstract that the candidate intends to present during the school. 3. *Letter of recommendation*: A brief letter from the academic advisor or the employer of the candidate supporting her/his application. Please also indicate if additional support would be required to attend the school. *Application submission*: Please use the following EasyChair web link:* Application Submission <https://easychair.org/conferences/?conf=soair2019>.* *IV. Important Dates * 1. Application submission *[Extended]*: *10-January, 2019 * 2. Notification of acceptance: *14-January, 2019 * 3. Spring School: *17-24 March, 2019* *V. Organizers * 1. *Amir Aly *– Ritsumeikan University – Japan 2. *Franziska Kirstein *– Blue Ocean Robotics, Denmark 3. * Shashank Pathak *– Visteon Corporation, Germany --------------------- *Amir Aly, Ph.D.* Senior Researcher Emergent Systems Laboratory College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577 Japan

Dec. 26, 2018

Post-doc vacancies in Lisbon

by Prata, Diana

Two new Post-Doc positions opened at the Biomedical Neuroscience Lab (https://dpratalab.wordpress.com/; PI: Dr Diana Prata, with double affiliation in King’s College London), at the University of Lisbon - for research in human social neuroscience and the oxytocin system in a 3 year project. Expertise in fMRI and/or EEG highly preferred; and in eye-tracking and SCR favourable; with negotiable salary. Open until 28th of Dec 2018. Please apply or divulge. We look forward to welcoming you!: http://www.eracareers.pt/opportunities/index.aspx?task=global&jobId=106522 Diana Prata, Phd Marie Curie Fellow Principal Investigator (Biomedical Neuroscience Lab), Instituto de Biofísica e Engenharia Biomédica, FCUL Visiting Lecturer, IoPPN, King's College London

Dec. 25, 2018

Groningen Spring School on Cognitive Modeling

by Jelmer Borst

Fourth Groningen Spring School on Cognitive Modeling – ACT-R, Nengo, & PRIMs – Date: April 8-12, 2019 Location: Groningen, the Netherlands Fee: € 250 (late fee after February 15 will be € 300) More information and registration: www.cognitive-modeling.com/springschool We are happy to announce the fourth Groningen Spring School on Cognitive Modeling (April 8-12, 2019). This year, the Spring School will cover three different modeling paradigms: ACT-R, Nengo, and PRIMs. Moreover, we are finalising a fourth tutorial on error-driven learning, more details on that will follow soon. Each day will consist of theory lectures, one on each paradigm. Each modeling paradigm also includes hands-on assignments. Although students are free to choose the number of lectures they attend, we recommend students to sign up for lectures on two of the modeling paradigms, and complete the tutorial units for one of the paradigms. At the end of most days there will be a plenary research talk, to show how these different approaches to modeling are applied. On the first day, spring school students are asked to present their own research in a poster session. Like last year, we again offer the opportunity for project students to attend. The idea is that you have attended the spring school in an earlier year and now come back in the week of the spring school to work on your own modeling project under our supervision. Registration is now open. Admission is limited, so register soon! See the website www.cognitive-modeling.com/springschool for more information. Please feel free to forward the information to anyone who might be interested in the Spring School. ______________ ACT-R Teachers: Jelmer Borst & 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 (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: http://www.ai.rug.nl/~niels/actransfer.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. -- Jelmer Borst Assistant Professor University of Groningen Dept. of Artificial Intelligence E: j.p.borst(a)rug.nl W: http://www.jelmerborst.nl/

Dec. 24, 2018

A databank for intracellular electrophysiological recordings of adult somatosensory cortex

by Fleur Zeldenrust

Dear all, It is our pleasure to share with you a large database of whole-cell intracellular recordings from 315 neurons located in the supragranular layers (L2/3) of the primary somatosensory cortex in adult mice (9-45 weeks old) from both sexes (females, N=195; males, N=120). Data include 361 somatic current-clamp (CC) and 476 voltage-clamp (VC) experiments, recorded using a step-and-hold protocol (CC, N=257; VC, N=46), frozen noise injections (CC, N=104) and triangular voltage sweeps (VC, 10 (N=132), 50 (N=146) and 100 ms (N=152)), from regular spiking (N=169) and fast-spiking neurons (N=66). We believe that this database will particularly benefit computational modellers, as the data can be used to systematically study the properties of somatic integration, and the principles of action potential generation across sexes and across electrically characterised neuronal classes in adulthood. Understanding the principles of the somatic transformation of postsynaptic potentials into action potentials will shed light onto the computational principles of intracellular information transfer in single neurons and information processing in neuronal networks, helping to recreate neuronal functions in artificial systems. So feel free to use the data for your (cortical) cell models! The data can be found here: http://gigadb.org/dataset/100535 The paper can be found here: https://doi.org/10.1093/gigascience/giy147 Best regards and happy holidays, Angelica da Silva Lantyer Niccolò Calcini Ate Bijlsma Koen Kole Melanie Emmelkamp Manon Peeters Wim J. J. Scheenen Fleur Zeldenrust Tansu Celikel -- Fleur Zeldenrust Assistant Professor Department of Neurophysiology Donders Institute for Brain, Cognition and Behaviour Faculty of Science, Radboud University Heyendaalseweg 135, postvak 33, kamer 02.204 6525 AJ Nijmegen, the Netherlands tel +31 24 36 53195 fleurzeldenrust.nl

Dec. 24, 2018

SSCND9 - Call for applications

by Richard Naud

Dear comp-neuro, We are happy to announce the ninth Summer School of the Centre for Neural Dynamics<http://www.neurodynamic.uottawa.ca/summer.html> At the University of Ottawa May 26 - June 7, 2019 The course is intended for graduate students and undergraduate students in their third and fourth year of study in the physical sciences (e.g. physics, applied mathematics, engineering, computer science) and the life sciences (e.g. neuroscience, biology, physiology, human kinetics) who wish to develop their skills in neural data analysis and in mathematical modeling of neural activity. The topics will range from cellular to systems neuroscience, with applications in medicine. Individuals outside of academia may also participate. The first week will consist of 3 hours of lectures in the mornings followed by an afternoon of relatedcomputer-based laboratories. The second week will consist of 3 hours of lectures in the mornings, followed by an afternoon of interactive discussions and brainstorming activities. Each day will focus on a different subject in systems neuroscience and/or medicine. Participants will work in small groups with mentors, and will be prepared for these activities by directed readings. Later in the afternoon, groups will convene into a plenary session with our experts to identify proper computational questions and associated timely research projects on the focus theme. All classes will be held on the main downtown campus of the University of Ottawa. The course can also be taken for credit, since it is a University of Ottawa three-credit graduate course (NSC8104). The mark will be based on work done in the computer laboratories and a project. All students receive a letter stating that they satisfactorily participated in the school, regardless of whether they take the course for credit. Those taking it for credit will receive their mark from the University of Ottawa Registrar's Office later in the summer. Important Dates January 6, 2019: Registration opens. February 15, 2019: Application deadline (including letter of recommendation). Faculty * Prof. André Longtin (uOttawa) * Prof. Richard Naud (uOttawa) * Prof. John Lewis (uOttawa) * Prof. Jean-Philippe Thivierge (uOttawa) * Prof. Jean-Claude Béïque (uOttawa) * Prof. Maurice Chacron (McGill) * Prof. Jonathan Rubin (U Pitt) * Prof. Simon Chen (uOttawa) * Prof. Blake Richards (McGill,MILA) * Prof. Steve Prescott (U Toronto) * Dr. Saskia De Vries (Allen Institute) Organizers André Longtin Richard Naud John Lewis

Dec. 21, 2018

MSc and PhD programmes in Computational Neuroscience

by Mark van Rossum

Dear all Applications are invited for our new MSc and PhD programmes in Computational Neuroscience in Nottingham. https://www.nottingham.ac.uk/pgstudy/courses/psychology/computational-neuro… https://www.nottingham.ac.uk/pgstudy/courses/doctoral-training-programmes/e… Merry Christmas and a happy 2019 -- Mark van Rossum, Professor, Schools of Psychology and Maths, U Nottingham Psych Bldg Rm LG.19, +44-115-74-86851, +44-7722049644(m) This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

Dec. 21, 2018

A review of the year in (systems) neuroscience, from The Spike

by Mark Humphries

Systems neuroscience is a fascinating, if daunting, subject - daunting to keep up with, even more daunting to dive into for the first time That’s why I launched The Spike in 2016, as a platform to bring the triumphs and challenges of systems neuroscience to a broad audience As a great place to start, we’ve just published our review of 2018, https://medium.com/the-spike/2018-a-mildly-muddled-review-of-the-year-in-ne… And read the rest here: https://medium.com/the-spike Enjoy! Prof Mark Humphries @markdhumphries This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

Dec. 21, 2018

Faculty position in AI and Neuroscience, Cambridge

by Máté Lengyel

Faculty position in AI and Neuroscience Department of Engineering, University of Cambridge, UK Applications are invited for a University Lectureship (~ US Assistant Professor equivalent) at the intersection of Artificial Intelligence (AI) and Neuroscience (including Cognitive Science) in the Computational and Biological Learning Lab (cbl.eng.cam.ac.uk). CBL combines expertise in computational neuroscience and cognitive science (Mate Lengyel, Guillaume Hennequin, Rich Turner) and machine learning (Zoubin Ghahramani, Carl Rasmussen, Rich Turner, Jose Miguel Hernandez-Lobato). We particularly encourage applicants who would complement our current research activities. The successful applicant’s research should use AI-inspired computational and theoretical approaches to neuroscience (including computational cognitive science), or conversely, biological intelligence-inspired approaches to AI (with an emphasis on machine learning-based approaches), and may combine these approaches with behavioural experiments. This is a linked post offered in association with Wolfson College, and the successful applicant will be elected to an Official Fellowship of the College. Informal enquiries are welcome to: Mate Lengyel <m.lengyel(a)eng.cam.ac.uk> Guillaume Hennequin <g.hennequin(a)eng.cam.ac.uk> Richard Turner <ret26(a)cam.ac.uk> Timeline: - Closing date of applications: Friday, 1 February 2019 - Interviews: March-April 2019 - Decision expected: April 2019 Further information and details of the application process can be found at http://www.jobs.cam.ac.uk/job/19416/ The University of Cambridge values diversity and is committed to equality of opportunity. -- Mate Lengyel Professor of Computational Neuroscience Computational and Biological Learning Lab Cambridge University Engineering Department Trumpington Street, Cambridge CB2 1PZ, UK tel: +44 (0)1223 748 532, fax: +44 (0)1223 765 587 email: m.lengyel(a)eng.cam.ac.uk web: www.eng.cam.ac.uk/~m.lengyel

Dec. 20, 2018

Research positions in Neuromorphic computing in Singapore

by Yansong Chua

Multiple scientist and engineer positions are open for a neuromorphic program (on-going till 2021) in Singapore, at the Institute for Infocomm Research (I2R), A*STAR. The program is a multi-disciplinary effort, that straddles across the hardware (neuromorphic chip with RRAM, on-chip learning), middleware (emulator) and software (learning algorithms), and we aim to develop a demonstrating application system at end of the program. The program hence presents an unique research opportunity for candidates hoping to build a complete neuromorphic learning system. We are now in the second year of the program and have made good progress on all three aspects of the program. We have still a few openings for talented scientists and both software and hardware engineers who would be excited to work on any aspects of the program (hardware, middleware, software and system integration). Multiple top-ranked universities and research institutes in Singapore (NUS, NTU, IME, IHPC, I2R) are collaborating on the program. The work package I am in-charge of is primarily involved in the design of better algorithms for spiking neural networks. To this end, successful candidates will conduct research in one or more of the following areas: - Neuronal encoding: how to better encode external stimuli into spike based representations to facilitate decoding with high fidelity and also better learning performance (in terms of accuracy and power efficiency). - Supervised learning: given that spiking neural networks are asynchronous and sparse in their activities, the design of supervised learning algorithms that can fully capitalize on these properties becomes critical. - Mapping of state-of-art deep learning networks to spiking networks. Neuromorphic learning algorithms are still solving fairly simple problems compared to deep learning. For this, we would like to systematically borrow from the deep learning community networks and learning algorithms that can quickly boost the capabilities of spiking neural networks. - Unsupervised learning. STDP is well suited for unsupervised learning in spiking neural networks, and we would like to further advance STDP learning in spiking neural networks (both theory and applications). Preference will be given to candidates who can document knowledge in deep learning, spiking neural networks or signal processing (with interest in spiking neural networks). Candidates must have a PhD (for scientists) or MS/BS (for engineers) in computer science, computational neuroscience or related fields. Strong programming and quantitative skills are highly desired. Candidates should be proficient in spoken and written English. The appointment will be for 3 years, and extended for another 1 year, after review. Salaries are commensurate with internationally-competitive salaries and benefits. The start date is flexible and applications will be considered on a rolling basis until the positions are filled. Other benefits include: - Funding for international conferences and training courses - Collaboration opportunities with an excellent network of international scientists Candidates please send your curriculum vitae, a statement of research interests and three references to Dr. Yansong Chua (chuays(a)i2r.a-star.edu.sg)

Dec. 19, 2018

Joint A*STAR (Singapore) and King’s College London PhD Studentship

by Yansong Chua

We would like to encourage potential PhD candidates interested to work on understanding the role of stochastic neuron models in neuromorphic computing to apply for the above PhD studentship. We are including below a non-technical introduction to the project involved. The candidate will be jointly supervised by Prof. Osvaldo Simeone, Professor of Information Engineering, King's College London and Dr. Yansong Chua, Institute for Infocomm Research, A*STAR. For further queries, we maybe reached at: Prof Simeone: osvaldo.simeone at kcl.ac.uk Dr Chua: chuays at i2r.a-star.edu.sg More application details are also available at https://www.kcl.ac.uk/research/funding-opportunities/doctoral-research-oppo… https://www.kcl.ac.uk/research/funding-opportunities/doctoral-research-oppo… For all its recent breakthroughs, modern machine learning based on deep neural networks is becoming increasingly unaffordable in terms of computing and energy resources needed to run training algorithms that achieve state-of-the-art performance. This poses possibly insurmountable challenges for the implementation of efficient learning methods on resource-limited devices such as smart sensors or wearables. A possible solution to this problem is the adoption of the new paradigm of neuromorphic computing, which relies on energy-efficient sparse spike-domain processing and communication that are inspired by the operation of the brain. Whether Spiking Neural Networks (SNNs) can overcome the limitations of conventional deep networks for the implementation of low-power machine learning is a fundamental question that is currently being investigated by major technology companies and universities. In this project, this issue will be tackled both theoretically and through hands-on experiments by leveraging the complementary expertise of the respective research teams at KCL and A*STAR. Specifically, this research will seek to understand whether conventional deterministic models for SNNs can be improved by probabilistic models, which are typically used in neuroscience to model the brain operation, in terms of accuracy, speed, and robustness. In the first two years, at KCL, the project will concentrate on deriving models and learning rules for probabilistic SNNs. In the last two years, at A*STAR, the research will shift to aspects related to implementation, with a focus on the comparison between deterministic and probabilistic SNNs and on the use of nano-scale devices for the implementation of probabilistic SNNs.

Dec. 19, 2018