[visionlist] PostDoc positions on deep learning | Brown University

Thomas Serre thomas_serre at brown.edu
Mon Jan 7 16:13:59 -05 2019

PostDoc positions on deep learning
Brown University

The Serre lab has openings for two postdoctoral fellows. One project will focus on modeling temporal data with recurrent neural networks with applications to neural prosthetics and brain-computer interface (in collaboration with David Borton, http://borton.engin.brown.edu). The other project will focus on computational modeling at the intersection between vision, memory and reinforcement learning (co-mentored with Michael Frank, http://ski.cog.brown.edu). See our website at http://serre-lab.clps.brown.edu for more details about our research.

Relevant publications:

D. Linsley, J. Kim, V. Veerabadran, C. Windolf & T. Serre. Learning long-range spatial dependencies with horizontal gated-recurrent units. Neural Information Processing Systems, 2018. https://neurips.cc/Conferences/2018/Schedule?showEvent=11042

D. Linsley, D. Schiebler, S. Eberhardt & T. Serre. Learning what and where to attend. International Conference on Learning Representations, 2019. https://openreview.net/forum?id=BJgLg3R9KQ

Linsley, Drew, Junkyung Kim, David Berson, and Thomas Serre. Robust neural circuit reconstruction from serial electron microscopy with convolutional recurrent networks. arXiv, 2018. http://arxiv.org/abs/1811.11356

The successful candidate will become involved in a number of projects, depending on their particular interests, and will also have the opportunity to develop independent projects. The fellows will be located in a new state-of-the-art facility within the Carney Institute for Brain Science and embedded within the Carney Initiative for Computation in Brain and Mind. We also expect synergies with the Data Science Initiative co-located within the same building.

Requirements: Candidates must have a strong background in computer vision and/or computational neuroscience and/or machine learning, with a track record of relevant publications at top venues (e.g., NIPS, ICML, CVPR, ICCV, ICLR, etc.) Excellent python programming skills and tensorflow experience are required.

Application: Please send your application to thomas_serre at brown.edu with the subject line "postdoc position." Please include a brief statement of interests, a curriculum vitae, 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.

** About the Carney Initiative for Computation in Brain and Mind **
The Carney Initiative for Computation in Brain and Mind (CICBM; http://compneuro.clps.brown.edu), which began Fall 2013 as a component of the Brain Institute, 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. 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 members 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.
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