Open Postdoc position

Open Postdoc position

Our Computational Neuroscience Lab at the Institute for Cognitive & Neuroscience and Learning at the Beijing Normal University (BNU) has an opening for a postdoc working in the field of computational neuroscience. Our lab is interested in neural model building, neural information
processing, and data analysis in close collaboration with experimentalist in the areas of neural correlates of perceptual learning in the visual cortex in monkeys, multisensory integration, critical period plasticity in mice, motion integration, group learning in fish, and others. We have very close ties with a number of experimental groups on the campus, including 4 active awake monkey labs, eager to share data. There are thus various possible research projects for a computational postdoc interested in data analysis and model building in close collaboration with experiments.

We invite applications from prospective postdocs with background in a computational discipline, such as computational neuroscience, computer science, biophysics, computer vision, or machine learning. Former experience working with neuroscience data is of advantage.

The position is open immediately and supported by the Chinese government for 2 years and especially encourages non-Chinese applicants. Eligible candidates must have a recent PhD from a renowned university, strong publication record, fluent English proficiency and have to be
younger than 35. Salary is very competitive and adjusted to an international level. Chinese knowledge is no requirement but willingness to learn would help in daily life.

The Cognitive & Neuroscience and Learning Institute is a government supported research facility with one of the strongest neuroscience clusters in China. It is located within the urban center of the vibrant city of Beijing with a multitude of attractions and active night life.

For more infos on research, see

If you are interested and qualified, please send a cover letter, CV, transcripts of relevant publications to malte.rasch’@’ or wusi’@’