22 biosignal-processing-machine-learning Postdoctoral positions at Harvard University
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modern machine learning and a strong record of research accomplishment who are excited to build brain foundation models and other AI systems that advance our understanding of neural activity, brain
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. Specifically, our core technique is scanning electrochemical cell microscopy (SECCM) , a powerful electrochemical imaging method for probing electrochemical processes at nanoscale sites on complex electrodes. We
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awards in more than 120 countries for U.S. citizens to teach, conduct research, and carry out professional projects around the world. Location, activity type, and eligibility vary across awards
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, researchers, and students on foundational machine learning and biologically informed scientific applications. The position is particularly well-suited to candidates eager to apply their technical expertise in
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diverse, inclusive community dedicated to alleviating suffering and improving health and well-being for all through excellence in teaching and learning, discovery and scholarship, and service and leadership
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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, Diffusion models, Reinforcement Learning. The successful candidate will work in a highly collaborative and international environment. Contact Information: For further information, please contact petros
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for opportunities abroad. These grants present an excellent opportunity for recently minted scholars to deepen their expertise, to acquire new skills, to work with additional resources, and to make connections with
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teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. The University, which is based in Cambridge and Boston, Massachusetts, has an enrollment
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are desirable. We particularly encourage applicants with expertise in Multi-scale Modeling, Evolutionary Computation, Diffusion models, Reinforcement Learning. The successful candidate will work in a highly