15 PhD, 4 Postdocs, 9 associate prof. positions
PhD psotitions : 6 offers
 Research Associate /Senior Research Associate positions, University of Bristol, UK
 Postdoc position in Computational Neuroscience at the CRM, Barcelona, Spain
 1 research associate and 2 funded PhD positions on the evolution of neural learning and plasticity, Loughborough University, UK
 Two PhD Student Positions in Computer Vision for Learnings Systems at MPI-IS, Tuebingen, Germany
 Postdoctoral Scholars in Computational Brain Science – Brown Institute for Brain Sciences, Providence, RI
 Postdoctoral Research Associate in Neural Engineering, University of Essex, UK
PhD and Research Fellows Positions in Machine Learning / Deep Learning, Hochreiter Group, Linz - Austria
 10 PhD Positions in Machine Learning / Deep Learning, Hochreiter Group, Linz, Austria
 Five Research Fellows in Machine Learning / Deep Learning, Hochreiter Group, Linz, Austria
 Two Research Fellows in Machine Learning / Deep Learning, Hochreiter Group, Linz, Austria
 Post doc position in comparative cognition (4-yrs), Vienna, Austria
 PhD call for applications PROPOSAL OF SUBJECT OF THESIS - New Stochastic Optimization Approaches to the Aerospace Vehicle Spatial Design Problem
 De : Jeffrey Bowers <J.Bowers[at]bristol.ac.uk>
Research Associate /Senior Research Associate positions, University of Bristol
Salary: £32,548 to £41,212 per annum
Deadline: 20th August 2018
We are seeking to appoint talented computational modelers to join an ERC-funded project entitled “Generalisation in Mind and Machine”. The project explores how well neural networks support human-like generalisation across a range of tasks. Two postdoctoral fellows and two PhD students are working on project, and we are looking to hire two more persons with PhDs (or potentially BSc) in computer science or cognitive psychology (or a related field) with experience working with neural networks.
In contrast with the large community of researchers focused on improving the performance of deep networks for applied reasons, the goal of this project is to explore what neural networks tell us about how the brain works. More specifically, the team will be working on questions of generalisation in the domains of object identification, word identification, short-term memory, and games, amongst other areas. A core issue is whether networks need to be include symbolic computations to succeed on some forms of generalisation. For overview of some of the issues we are exploring in the project see: Bowers, J. S. (2017). Parallel Distributed Processing Theory in the Age of Deep Networks. Trends in Cognitive Sciences, 12, 950-961. For more details regarding the project see our ERC website:http://mindandmachine.blogs.bristol.ac.uk/
This post is available from Oct 1st 2018 (but somewhat flexible about start date) and currently has funding secured until Oct 1st 2021. To apply go to: https://www.jobs.ac.uk/job/BKR397/erc-research-associate-senior-research-associate/ If you have any questions, please get in touch with Jeff Bowers at: j.bowers[at]bristol.ac.uk
 De : Klaus Wimmer <kwimmer[at]crm.cat>
A fully funded POSTDOC POSITION in computational neuroscience is available in the lab of Klaus Wimmer, Computational Neuroscience Group at the CRM, Barcelona, Spain.
We are looking for an enthusiastic and scientifically curious researcher with a strong interest in computational neuroscience. The perfect candidate has a strong mathematical, physical or engineering background, scientific programming skills (Matlab, Python), and a keen interest in biological neural systems. Knowledge in computational neuroscience, dynamical systems, machine learning or advanced statistics is a plus. Good team spirit is a must.
The neural basis of decision making and working memory has been studied extensively, yet our understanding of how distributed circuits in the brain perform these cognitive functions is only at the beginning. Models of cortical circuits can shed light on the underlying neural network dynamics. The Postdoc will work on building such models and on cutting-edge analysis of large-scale neural activity recordings (neuronal population recordings, fMRI, EEG).
The Computational Neuroscience Group is based at the Centre de Recerca Matemàtica at the campus of the Universitat Autònoma de Barcelona. It is a joint effort of Alex Roxin and Klaus Wimmer, and forms part of a larger network of theoretical and systems neuroscience labs in Barcelona. The successful candidate will benefit from a vibrant and stimulating research community and will have the opportunity of enjoying a lively city.
More information can be found at: https://sites.google.com/view/wimmerlab
How to apply
Interested candidates should e-mail their application as a single pdf file to Klaus Wimmer, kwimmer[at]crm.cat, with the subject “Postdoc 2018”. The application should include: (1) CV with publication list, (2) a brief description of research experience and interests, (3) contact information for two references.
The position is available immediately and applications will be accepted until it is filled. Informal inquiries are welcome.
Ramón y Cajal researcher at
Centre de Recerca Matemàtica
Campus de Bellaterra, Edifici C
08193 Bellaterra (Barcelona)
Tel. +34 935 86 85 15
 De : Andrea Soltoggio <A.Soltoggio[at]lboro.ac.uk>
1 research associate and 2 funded PhD. postions on the evolution of neural learning and plasticity
One research associate and two funded Ph.D. positions are available at the Computer Science Department, School of Science, Loughborough University, UK, on the topics of the evolution of lifelong learning in neural networks.
Research. The aim is to develop new neuroevolution algorithms for lifelong learning. The objectives are to devise machine learning systems that autonomously adapt to changing conditions such as variation of the data distribution, variation of the problem domain or parameters, with minimal human intervention. The approach will use neuroevolution, neuromodulation, and other methodologies to continuously discover and update learning strategies, implement selective plasticity, and achieve continual learning.
For an overview of the research direction, see the paper: Born to Learn: the Inspiration, Progress and Future of Evolved Plastic Artificial Neural Networkshttps://www.researchgate.net/publication/315710249_Born_to_Learn_the_Inspiration_Progress_and_Future_of_Evolved_Plastic_Artificial_Neural_Networks
Application areas include a variety of automation and machine learning problems, e.g. vision, control, and robotics, with a particular focus on resilience and autonomy.
Working environment. The research associate and Ph.D. students, based at the Computer Science Department, will work in an international team with opportunities for collaboration and travel. They will have access to a number of robotic platforms such as mobile and flying robots, manufacturing robots, High Performance Computing clusters, and GPU computing. The Computer Science Department and robotics laboratories have ongoing collaborations with large industries and programs to promote start-ups.
Loughborough University is ranked 7th in the UK in the 2019 League Table Ranking http://www.thecompleteuniversityguide.co.uk/loughborough/performance ), and is located in Loughborough, a town well connected to London by a 1h20m journey by train.
Postdoc: A Ph.D. in Computer Science or related with a strong publication record, coding abilities, predisposition to work in a team and independence, passion for science, solid work ethics.
Ph.D. students: The ideal candidate holds (or is about to obtain) a first-class honour undergraduate/postgraduate degree (or equivalent) in Computer Science, Mathematics, Statistics, Electrical or Electronic Engineering, or has authored publications in recognised conferences/journals. Independent working skills are valued as well as the capability of working in a team. Collegiality and interpersonal skills are essential.
Excellent English language skills are also essential (see requirements herehttp://www.lboro.ac.uk/international/englang/index.htm)
Period and salaries.
Postdoc position: until June 2020 (with possible extension) with a competitive salary at Grade 6 (http://www.lboro.ac.uk/services/hr/benefits/pay-rewards/)
Start: as soon as possible.
Scholarship: £14,777 per annum plus tuition fees at the UK/EU rate.
Start: August 2018 or shortly after.
Duration: 3.5 years.
Enquiries and applications. Interested candidates are invited to send preliminary enquiries to a.soltoggio[at]lboro.ac.ukincluding a CV, a university transcript of marks, a list of references, and a statement of about 300 words motivating their interest in this area of research.
Dr. Andrea Soltoggio
Lecturer in Artificial Intelligence
Department of Computer Science,
Centre for Data Science,
Centre for Information Management
Haslegrave Building, N.2.03
LE11 3TU, UK
Phone: +44 (0) 1509 635748
 De : Joerg Stueckler <joerg.stueckler[at]tuebingen.mpg.de>
Two PhD Student Positions in Computer Vision for Learnings Systems
within the Embodied Vision Group at the Max Planck Institute for Intelligent Systems in Tuebingen, Germany
The Embodied Vision Group at the Max Planck Institute for Intelligent Systems investigates novel methods for autonomous systems to learn dynamic scene understanding and to use this understanding to perform complex tasks such as navigation or object manipulation. We aim at systems that learn from raw sensor measurements like images or tactile information and through action within their environment. A research focus in this context is on computer vision topics, including
- Physical and 3D dynamic scene understanding
- Learning of predictive environment models
- Self-supervised and online visual and multi-modal learning
- Vision-based interactive perception and learning for object manipulation
- Vision-based navigation for drones and mobile robots
- Deep reinforcement learning
We are looking for two PhD students who are holding an outstanding Master’s degree in the computer or natural sciences, electrical or control engineering or applied mathematics. The PhD students will conduct research in one or several of the above topic areas.
- Candidates should have studied areas related to computer vision and machine learning.Areas of particular interest for us at the moment are deep learning, visual scene understanding, visual/visual-inertial simultaneous localization and mapping, 3D scene reconstruction, robot vision, robot learning and deep reinforcement learning.
- Successful candidates will typically have ranked at or near the top of their classes and be highly proficient in written and spoken English.
- Excellent computer science skills as well as a strong mathematical background are required.
- Prior research experience in computer vision, deep learning, robotic object manipulation or autonomous navigation is a plus.
The PhD students will receive a PhD funding contract with an initial duration of 3 years. The position is funded for 3-4 years. Salary will be based on previous experience according to guidelines of the German Collective Wage Agreement for the Public Service (TVöD). The earliest start date is August 1st, 2018.
The Max-Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. The Max-Planck Society seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply.
The Embodied Vision Group (https://ev.is.mpg.de) is a newly established research group at the Max Planck Institute for Intelligent Systems in Tuebingen, Germany, and is lead by Dr. Joerg Stueckler. The institute is a world-class center for foundational research in machine learning, computer vision, robotics and material science. Tübingen is a scenic medieval university town, cradled in what is simultaneously one of Germany’s most beautiful landscapes in one of Europe’s most economically successful areas. The working language at the institute is English.
How to apply
Applications and inquiries should be sent quoting reference number 33.18 to Dr. Joerg Stueckler (see contact details below). Applications must be submitted by email as a single pdf (max. 10 MB) and include a CV, motivation letter with research statement, publication list, transcripts of BSc and MSc degrees, and contact details of 2-3 references. Optionally, up to 2 selected own publications or theses can be included in a second pdf (max. 5 MB). Applications should also indicate earliest date of availability.
There is no fixed application deadline; applications are considered until the positions have been filled or are no longer needed. Preference will be given to applications received before July 15th, 2018.
For further details on the positions and how to apply, please visit
Please liberally forward this announcement and share to possibly interested candidates or persons who might know suitable candidates.
Dr. Joerg Stueckler
Max Planck Research Group Leader
Embodied Vision Group
Max-Planck-Institute for Intelligent Systems
 De: Thomas Serre <thomas_serre[at]brown.edu>
The Frank and Serre labs at Brown university are seeking applicants for the Paul J. Salem Postdoctoral Scholarships in Brain Science. The postdoctoral fellow will lead an exciting new project at the interface between machine learning and neuroscience. In particular, we are looking for computational neuroscience and machine learning experts interested in the intersection between vision, memory and reinforcement learning. Relevant projects in the two groups can be seen in the following example works:
• Franklin, N.T. & Frank, M.J. (2018). Compositional clustering in task structure learning. PLOS Computational Biology, 14(4): e1006116. http://ski.clps.brown.edu/papers/FranklinFrank_Compositional18.pdf
• Nassar, M.R., Helmers, J. & Frank, M.J. (2018). Chunking as a rational strategy for lossy data compression in visual working memory. Psychological Review. http://ski.clps.brown.edu/papers/NassarHelmersFrank_chunking.pdf
• Drew Linsley, Junkyung Kim, Vijay Veerabadran, Thomas Serre. Learning long-range spatial dependencies with horizontal gated-recurrent units. 2018 https://arxiv.org/abs/1805.08315v1
• Drew Linsley, Dan Scheibler, Sven Eberhardt, Thomas Serre. Global-and-local attention networks for visual recognition. 2018 https://arxiv.org/abs/1805.08819v1
Candidates are expected to have a solid background in one or more of the following domains: modern machine learning, computational models of neural dynamics underlying perceptual or cognitive processes, signal processing. In addition, to conducting primary research with neural networks, candidates will be involved in the mentoring of students, and will participate in workshops and challenges at the interface between machine learning and neuroscience (see e.g., http://compneuro.clps.brown.edu/datathon_2017/and http://compneuro.clps.brown.edu/2018-modeling-competition/).
The initial appointment is for 12 months, renewable for another year, and potentially longer depending on funding. The start date is negotiable though an early start is strongly preferred. Salary is commensurate with experience and is competitive. We encourage Salem Scholars to seek external funding during their appointment, as a critical component in their professional development.
Candidates must have received their PhDs within 3 years of the application deadline, and will work under the supervision of Drs Frank and Serre who are affiliated with the Carney Initiative for Computation in Brain and Mind. They must have a strong background in computational neuroscience and machine learning, with a track record of relevant publications at top venues (such as NIPS, ICML, PLOS Computational Biology, etc). Excellent programming skills are required (e.g., C/C++/Matlab/Python/R).
Please send your applications by email to michael_frank[at]brown.edu thomas_serre[at]brown.edu. Please include a brief statement of interests, a curriculum vita, a list of publications and the name of 2-3 reference writers (no letter needed at this stage). There is no deadline for the application but applicants are encouraged to apply as soon as possible as the position will be filled as soon as a suitable applicant is found.
The Carney Initiative for Computation in Brain and Mind (CICBM; http://compneuro.clps.brown.edu), which began Fall 2013 as a component of BIBS, is an energetic and enthusiastic effort that fosters synergistic collaborations across departments. Groups affiliated with the initiative work on two core levels of computation. The first level focuses on theoretical neuroscience, including computational perception, control over action and learning, and fundamental questions in neuronal networks (synaptic plasticity, circuits, networks, oscillations). The second level focuses on applications and neurotechnology, including brain-machine interfaces, advanced neural data analysis, computer vision, computational psychiatry, and robotics. CICBM has 16 core computational faculty (http://compneuro.clps.brown.edu/people/) spanning six departments, and many more faculty who incorporate computation for theory development, analysis, or both. Computational neuroscience tools at Brown have been applied in projects including brain-machine control of robotic arms in paralyzed humans; models of visual systems in biological organisms and their innovative application for classifying animal behavioral patterns; predicting and quantifying effects of genetics, disease, medications, and brain stimulation on motor and cognitive function; identification of the source of neural rhythms and their roles in sensorimotor function; development of fundamental theories of brain plasticity, and learning; state-of-the art models of machine learning and reinforcement learning in computer science.
The Carney Institute for Brain Science at Brown University advances multidisciplinary research, technology development, and training in the brain sciences and works to establish Brown University as an internationally recognized leader in brain research. The institute was just endowed with a new $100 million gift. CIBS unites more than 100 faculty from a diverse group of departments at Brown, spanning basic and clinical departments, and physical and biological sciences. CIBS provides a mechanism to advance interdisciplinary research efforts among this broad group. CIBS provides essential support to obtain and administer multi-investigator grants for research, infrastructure, and training. The Institute actively seeks new training funds to support interdisciplinary education that transcends that available in individual academic departments.
Thomas Serre | GMT -5:00 EDT | T: +1 401-484-0750
Associate Professor of Cog Ling & Psych Sciences | Brown University
URL: goo.gl/G69SaF | Google Talk: tserre | Skype: thomas.serre