15 machine-learning-"https:"-"https:"-"https:" Postdoctoral positions at Harvard University
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will lead and participate in observations and data analysis across the electromagnetic spectrum, or will lead work on machine learning classification of optical transients. Applicants with previous
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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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data in near-term era quantum computers. Applicants with backgrounds in quantum information or particle physics are both encouraged to apply. Candidates with strong expertise in machine learning, quantum
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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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deep expertise in modern machine learning and a strong record of research accomplishment who are excited to advance foundation models, agentic systems, and new AI approaches for high-impact scientific
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on type, size, location of data centers in the US, their electricity and water demand, carbon emissions; exposure to air pollution. ● Develop and/or apply methods for causal inference and machine learning
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Science Statistics / Biostatistics Applied Mathematics Data Science Demonstrated expertise in modern machine learning, including at least one of the following: Deep learning (e.g., transformers, sequence models
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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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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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in internal meetings and at national/international conferences. ● Collaborate with an interdisciplinary team (bio)statisticians, data scientists, computer scientists, and climate scientists