The Cognitive & Systems Neuroscience group of the Swammerdam Institute for Life Sciences (SILS) is seeking a highly qualified and motivated Assistant Professor to conduct collaborative research and teaching in Computational Neuroscience. The candidate will focus on computational modelling in the context of a recently proposed theoretical framework on representation, consciousness and multimodal integration in the brain, and will in addition develop methods for advanced analyses of neural data gathered by e.g. ensemble recordings and population imaging with cellular resolution.
The first key objective of this position is to conduct research and teaching in computational modelling in a framework defined by multisensory integration, construction and neural coding of representations in different brain states, including consciousness, sleep and anesthesia. Secondly, data analysis will be advanced by methods outlined by related key words such as population coding, coherence and communication, measures of integration and information transfer, attractor dynamics and representational capacity. These research topics will be reflected in teaching at Bachelor, Master and PhD levels, connecting Computational Neuroscience with systems and cognitive neuroscience subjects such as perception, memory, decision-making and awareness. The Assistant Professor will connect his/her work to other experimental and theoretical work performed in Cognitive and Systems Neuroscience and related groups at SILS. Additional objectives of this position are to support programming activities (mostly in Matlab/Python), data exchange with collaborating labs and management of research and teaching.
Applicants should hold a PhD degree in computational neuroscience or related field, including machine learning, mathematics, physics or biomedical engineering. They have postdoctoral research experience in this field as testified by significant publications. Candidates are further required to have a strong background in theoretical neuroscience, and express their competence in computational neuroscience through experience in programming, neural simulation, theoretical models, neural data analysis, high-performance computing and web-based tools. Demonstrable experience and affinity with multi-neuron recordings and related neurophysiology, cognition and systems neuroscience are important assets for this position. Experience in academic teaching in the subject field is mandatory and the candidate should be able to teach in the Dutch language after 3 years of employment. Affinity with management, organization and engagement in large-scale European research consortia is preferred.
All permanent staff are required to have a University teaching qualification (the so-called BasisKwalificatie Onderwijs, BKO). If the successful candidate does not yet have this qualification, it should be obtained during the probation period.