-
, or applied mathematics that could drive the frontier of biomedical research. The role will be focused on the development of novel computational and algorithmic methods, with a strong bent towards developing
-
in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
-
Qualifications: Doctoral degree. Applicants background may include studies in: Computational Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications: Expertise (or desire
-
—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
-
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
-
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
-
related field: Computer Science Statistics / Biostatistics Applied Mathematics Data Science ● Demonstrated expertise in modern machine learning, including at least one of the following: Spatiotemporal
-
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
-
, 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
-
, statistics, or applied mathematics that could drive the frontier of biomedical research. The role will be focused on the development of novel computational and algorithmic methods, with a strong bent towards