354 machine-learning "https:" "https:" "https:" "https:" "https:" Fellowship research jobs
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Field
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of AI and in particular machine learning (ML). As today’s mainstream AI/ML workloads often resort to large-scale and energy-hungry supercomputers, it is necessary have a more critical look at how HPC
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career development plans with formal supervision and project-based learning. Secondments, consortium meetings, and workshops will provide hands-on experience in collaborative modelling, scientific
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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analyzed with various Machine Learning and Data Science techniques to assess the dynamics involving case processing and costs. The first phase of the research will organize general data from the lawsuits
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educational system. Strong background in molecular modeling, molecular dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab
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dynamics simulations, or computer-aided drug design. Proven record of programming language through publicly available Github/Gitlab or similar repositories. Experience in the cell biology lab Fluent oral and
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opportunity to contribute to leading-edge research at the intersection of applied machine learning and clinical dental practice. As a member of our team, you will help translate contemporary data science
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of immune cell function. These projects are focused on making safer and more effective cell therapies (e.g., CAR-T) and gene therapies for cancer and beyond. We are an interdisciplinary lab spanning
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to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning to process tissue data reproducibly and at scale Conduct analyses using programming
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical