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exciting opportunities for machine learning to address outstanding biological questions. The postdoc to be recruited will be working on the development of machine learning methods for single-cell data. In
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questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and large language models
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statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft matter and nanomaterials
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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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specimens. The postdoc will contribute to the development of hybrid modeling and identification approaches that combine classical constitutive frameworks, numerical simulation, and machine learning. The work
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expertise in machine learning or computational modelling who are eager to advance conceptual innovation toward practical industrial deployment. Qualifications PhD in Computer Science, Machine Learning
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clustering, redshift-space distortions, weak/strong gravitational lensing, and artificial intelligence/machine learning (AI/ML). The observational focus is on optical sky surveys (DES, DESI, Roman, Rubin Obs
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player and great collaborator Strong interest in interdisciplinary work at the interface between neurodegeneration, modeling, screening and machine learning Prior experience in iPSC modelling and CRISPR
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About the Opportunity This job seeks a postdoc to work on one or more projects related to the development and assessment of wearable robotics. Possible projects topics include: Developing machine
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machine learning (ML), hydrologic and energy systems simulations, and scenario forecasting-to evaluate dynamic energy-water futures and resilience strategies for diverse Idaho communities. Job Summary/Basic