Dear Colleagues, dear all, We are inviting applications for 2 postdoc positions (for at least 2 years, earliest start April 1, 2016) in computational neuroscience at the University of Bern, Switzerland. Our research is devoted to models of synaptic plasticity and dendritic integration that serve as a computational paradigm for learning in neuronal networks. We have recently suggested to consider “Learning by the dendritic prediction of somatic spiking” (Neuron 2014) that assigns an intrinsic computational task to neurons and dendrites. This concept will be extended by including dendritic nonlinearities and considering networks of such neuronal prediction elements. The 2 positions are: 1) Postdoc for modeling dendritic integration. We have shown how the error-backpropagation algorithm translates to a dendritic tree that displays NMDA-spikes in individual dendritic branches (PLoS Comp Biol 2016). Along these ideas a biophysical model of dendritic integration will be worked out that makes also contact to Bayesian integration. 2) Postdoc for modeling synaptic plasticity and learning in networks. The neurons as intrinsic prediction elements will be connected to form a network that mimics various learning tasks and that is particularly suited for imitation learning. You will profit from generous travel funding and from collaborations in- and outside the Human Brain Project, and you will also enjoy the beautiful city and surrounding of Switzerland’s capital. Ideal candidates have a strong background in computational neuroscience and machine learning. Please send CV, letter of motivation, and publication list by March 11 to Walter Senn (senn@pyl.unibe.ch) and Sabine Herzog (herzog@pyl.unibe.ch). With best wishes Walter Senn PS: For recent work of our group see http://www.physio.unibe.ch/~senn/neuroscience.aspx