14 condition-monitoring-machine-learning Postdoctoral research jobs at University of Cambridge in Uk
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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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. 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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., orthotopic, patient-derived xenografts) to study cancer biology and therapeutic response. You will play a key role in helping establish, monitor and analyse in vivo models, working collaboratively with
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interactions in the condensed phase and at surfaces, with a particular emphasis on the development and application of first principles and/or machine learning approaches. Research in the Michaelides group
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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monitoring and profiling of breast tissue and systemic responses; Use of mouse models to study early tumour initiation; Application of single cell and spatial transcriptomics, lineage tracing, and multiomics
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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
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of reaction optimisation and synthesis of suitable reagents, test the conditions developed at the cellular level and purify and characterise (mass spectrometry) glycoRNA. The successful candidate will have (or
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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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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