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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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to join our team. Our lab focuses on developing and applying innovative statistical machine learning methods, single-cell multi-omics, and systems immunology approaches to investigate immune-mediated
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learning, and signal processing applied to conduct high quality research with a particular focus on neuropsychiatric and cardiovascular diseases. Working in a large team of 15 PhD students, several postdocs
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/Statistics, Medical/Health Informatics. Strong computational and programming skills with abilities to develop cutting-edge large-scale machine/deep learning algorithms using high-performance computing (HPC
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evaluation.This opportunity will prepare candidates for a range of competitive positions in academia or industry that involve computational biology/chemistry, machine-learning for biological or chemical data, and
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: 6468573 Postdoctoral Employee - Artificial Intelligence - Electrical Engineering and Computer Sciences Department Position overview Salary range: The UC postdoc salary scales set the minimum pay determined
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Qualifications: PhD in experimental particle physics at the time of appointment. Preferred: Deep understanding of the particle detectors, particle identification, data analysis Machine learning experience is a
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and the terms of the research grant when extending an offer. Completion of PhD in Data Science, Computer Science, Mathematics, or other discipline aligned with CDS faculty research by the start date
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Expertise in molecular, cellular, or microbial biology. Experience with computational biology approaches, including analysis of large-scale sequencing data. Background and strong interest in evolutionary
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postdoctoral and PhD researchers on the team*Interest in developing and applying Large Language Models (LLM) and spatial Machine Learning (ML) modelsSalary and full employee benefits are offered in accordance