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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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Qualifications: Doctoral degree. Applicants background may include studies in: Computational Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications: Expertise (or desire
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—are intended to foster the early career development of researchers who have transitioned or are transitioning from training environments in the physical/mathematical/computational sciences or engineering into
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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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Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications Expertise (or desire to work) in reduced order modeling, Causal inference and High Performance Computing
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related field: Computer Science Statistics / Biostatistics Applied Mathematics Data Science ● Demonstrated expertise in modern machine learning, including at least one of the following: Spatiotemporal
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possible. Basic Qualifications PhD in computer science, statistics, electrical engineering, applied mathematics, computational biology, or a related quantitative field required by the expected start date
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, full-time, at Harvard University. Remote work for this position is not possible. Basic Qualifications PhD in computer science, statistics, electrical engineering, applied mathematics, computational
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, applied mathematics, computational biology, bioengineering, biophysics, or a related quantitative field required by the expected start date. Candidates must have received their PhD on or after September 15