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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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emerging solid-tumor indications. This position is ideally suited for a recent PhD or MD/PhD graduate seeking hands-on training in CAR T cell engineering, patient-sample analysis, and translational
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duties as assigned. REQUIREMENTS: REQUIRED: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong programming skills. Strong background in machine
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integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing of grants and
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technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on the importance
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research projects in computer vision, machine learning, AI, and robotics. Projects may include physically-grounded AI guidance agents, modeling of multimodal data, and generative AI systems for situated
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managing large multimodal datasets, as well as contributing to analytical studies related to machine learning, clinical decision rules, and time-to-intervention evaluations. Responsibilities include curating
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and expanding team. You’ll play a key role in our success through your code, publications, and strategic promotion of our work. * PhD in Computer Science, Biomedical Informatics, Machine Learning
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of Alabama and beyond. The successful candidate will apply tools including (but not limited to) Data Acquisitions, Data Mining, Data Visualization, Machine Learning, Statistics, Optimization and Simulation in
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hydrodynamic modeling (e.g., SFINCS, DFLOW-FM, MIKE, ADCIRC), coastal hazard assessment, model coupling, or model calibration and validation. Experience in machine learning and statistical/probabilistic analysis