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(e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian
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. Familiarity with standard design verification (DV) procedures and continuous integration (CI) setups would be beneficial. Knowledge of machine learning workloads and the design of machine-learning accelerators
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology
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complex behaviours, including learning, in the small invertebrate model organism C. elegans. We have recently discovered a range of novel dopamine receptors in C. elegans and found that different receptors
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lab investigates systems neuroscience questions, specifically the role of cortico-subcortical loops in statistical learning. We focus on the auditory system and perform awake/asleep electrophysiology
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, at the University of Cambridge, UK. The Research Assistant will work together with a team of students and research collaborators on the development of learning-based control policies that facilitate
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modelling to study the causes and consequences of extreme chromosomal instability in these cancers. The role will involve: - Learning and applying cytogenetic methods for generation and analysis of chromosome