PhD/Postdoc position in Tübingen, Deep nets + human neurophysiology data
Dear colleagues, We have a position for a Ph.D. Student or Postdoctoral Researcher (m/f/d, E13 TV-L) in `Deep learning for studying population codes in the human brain’, starting as soon as possible. The initial fixed-term contract will be for 3 years with possible extension. Details at https://uni-tuebingen.de/en/196976. How do neural circuits in the human brain recognize objects, persons and actions from complex visual stimuli? To address these questions, we will develop deep convolutional neural networks for modelling how neurons in high-level human brain areas respond to complex visual information. We will make use of a unique dataset of neurophysiological recordings of single-unit activity and field potentials recorded from the medial temporal lobe of epilepsy patients. Our tools will open up avenues for a range of new investigations in cognitive and clinical neuroscience, and may inspire new artificial vision systems. The position is part of the BMBF-funded project DeepHumanVision in collaboration with the `Dynamic Vision and Learning’ Group at TU Munich (Prof. Dr. Laura Leal-Taixé) and the Cognitive and Clinical Neurophysiology Group at University Hospital Bonn (Prof. Dr. Dr. Mormann). Our group develop computational methods that help scientists interpret empirical data, with a focus on basic and clinical neuroscience research. We want to understand how neuronal networks in the brain process sensory information and control intelligent behaviour, and use this knowledge to develop methods for the diagnosis and therapy of neuronal dysfunction. We aim to work in an interdisciplinary, collaborative and supportive work environment which emphasizes diversity and inclusion. Tübingen has an internationally renowned research community in artificial intelligence, machine learning and computational neuroscience, including the Cyber Valley Initiative, the Tübingen AI Center, the Excellence Cluster Machine Learning, and the new MSc Program Machine Learning. We are situated in the AI Research Building, in close proximity to the Max Planck Institutes for Intelligent Systems and Biological Cybernetics, and participate in the two International Max Planck Research Schools (IMPRS) `Intelligent Systems’ and `Mechanisms of Mental Function and Dysfunction’. The position is open to candidates who have a PhD or Master’s in in a quantitative discipline (e.g. computer science, maths, statistics, physics, electrical engineering, computational neuroscience), a genuine interest in interdisciplinary work at the interface of machine learning and neuroscience, and strong programming skills (ideally Python/PyTorch). Prior experience in deep learning, and/or in analysing neurophysiological data with statistical methods is advantageous. The University seeks to raise the number of women in research and teaching and therefore urges qualified women academics to apply for these positions. Equally qualified applicants with disabilities will be given preference. The employment will be carried out by the central administration of the University of Tübingen. PhD applicants are also expected to apply to the IMPRS `Intelligent Systems’ https://imprs.is.mpg.de, Deadline also November 2. Please submit your application materials to mls-sekretariat@inf.uni-tuebingen.de, with subject `Application: Postdoc/PhD DeepHumanVision‘. Please include a CV, a brief statement of research interests, contact details of two referees and a work sample - anything that is genuinely your own work, e.g. a thesis, computer code, a research manuscript, an essay, or a publication. For postdoc applicants, we expect relevant prior publications. Application deadline: November 02, 2020. Best, Jakob Macke Prof. Dr. Jakob Macke Chair of Machine Learning in Science Excellence Cluster `Machine Learning: New Perspectives for Science’ Department of Computer Science University of Tübingen Adjunct Senior Research Scientist, Department of Empirical Inference Max Planck Institute for Intelligent Systems Tübingen Jakob.Macke@uni-tuebingen.de Office: Franziska Weiler, mls-sekretariat@inf.uni-tuebingen.de www.mackelab.org/tuebingen
participants (1)
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Jakob Macke