I am seeking candidates for fully funded postdoctoral and PhD positions in computational neuroscience at the University Medical Center Hamburg-Eppendorf (UKE). The successful candidates will conduct research in my computational laboratory (Institute for Neural Information Processing) at UKE: https://www.uke.de/english/departments-institutes/institutes/department-of-e... We will investigate, by developing and using advanced machine learning methods and neural network models, how populations of neurons (and of glia) in the brain encode information and use it to produce behaviors. We offer a wide range of interdisciplinary expertise in computational neuroscience. We also offers a high-quality and well-funded research environment including a network of international experimental collaborators such as Prof. Christopher Harvey at Harvard Medical School, Prof. Tommaso Fellin at IIT Italy, and Prof. Mriganka Sur at MIT. We seek candidates with a solid computational background and a keen interest in neuroscience. They must be highly motivated and creative individuals who want to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists. The job is available starting immediately and applications will be considered as soon as they are received and until the positions are filled. Funding is available for several years (with a minimum commitment of two years expected) for postdoc candidates and for the full duration of the PhD for PhD candidates. Interested applicants are strongly encouraged to email me (s.panzeri@uke.de or stefano.panzeri@gmail.com) as soon as possible, to inform me of the interest for the position and initiate a discussion about research projects. I suggest interested candidates to attach a CV when inquiring by email. For recent example publications from my lab, see: Dupret D et al (2025) Neural population activity for memory: properties, computations, and codes. Neuron: in press Safaai H et al (2025) Specialized structure of neural population codes in parietal cortex outputs. Nature Neuroscience 28, 2550–2560 Lorenz GM et al (2025) MINT: a toolbox for the analysis of multivariate neural information coding and transmission. PLOS Computational Biology 21 (4), e1012934 Kuan AT et al (2024). Synaptic wiring motifs in posterior parietal cortex support decision-making. Nature 627, 367–373 Celotto M, et al (2023) An information-theoretic quantification of the content of communication between brain regions. NeurIPS Panzeri S, et al (2022) The structures and functions of correlations in neural population codes. Nature Reviews Neuroscience 23:551-567 Koren V., Panzeri S (2022) Biologically plausible solutions for spiking networks with efficient coding. NeurIPS Curreli S, et al (2022) Complementary encoding of spatial information in hippocampal astrocytes. PLoS Biology 20(3): e3001530. Valente, M. et al (2021), Correlations enhance the behavioral readout of neural population activity in association cortex. Nature Neuroscience, 24, 975–986 Stefano Panzeri