148 estimation-methods "https:" "Computer Vision Center" Fellowship positions at Harvard University
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Details Title Postdoctoral Fellowship in Reinforcement Learning, Probabilistic Methods, and/or Interpretability School Harvard John A. Paulson School of Engineering and Applied Sciences Department
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Details Title Postdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems) School Harvard John A. Paulson School of Engineering
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of design and innovation on value creation for stakeholders. For more information on D^3/LISH , please visit https://d3.harvard.edu and https://d3.harvard.edu/lish/ . Research Focus: Postdoctoral Fellows
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sequence-function landscapes, using a combination of empirical data and ML methods (e.g. transformer models). One focus of this work will be on B-cell receptor evolution. Experience in applications of modern
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-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich
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statistical physics, biophysics, or in experimental method development including genomics and microfluidics. The successful candidate will work with Dr. Klein to develop an independent research project within
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position. We are most interested in applicants who have experience in computational methods development, in human genetics or a different field. Possible areas of research include: 1. Developing methods
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these methods to address challenges in scientific discovery and precision medicine. We seek highly-motivated applicants with background in one or more of the following areas: agentic AI, geometric deep learning
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 09-Mar-26 Location: Cambridge, Massachusetts Categories: Academic/Faculty Computer/Information Sciences Internal
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Patel’s group to produce highly impactful biomedical informatics research that presents new innovations in methods and novel findings that inform disease etiology. The candidate should be interested in