174 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" research jobs at Harvard University
Sort by
Refine Your Search
-
Listed
-
Program
-
Field
-
of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic
-
applications for a Postdoctoral Fellow with Professor Pragya Sur. Professor Sur’s lab focuses on research in high-dimensional statistics, machine learning theory, or more broadly, mathematical foundations of AI
-
to have a strong background in the foundations of machine learning. Special Instructions Required application documents include a cover letter, CV, a statement of research interests, and up to three
-
2). Vascular network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering The Disease Biophysics Group is a creative, transdisciplinary group of engineers
-
such as: Causal inference and the design and analysis of experiments Reinforcement learning and sequential decision-making Analysis of complex systems, networks, and large-scale data Machine learning
-
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
-
, and AI/machine learning would be helpful for the role. Experience with participant recruitment and retention as well as clinical human subject studies is a plus. Special Instructions Application
-
What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
-
astrophysics, exotic core-collapse supernovae, and machine learning methods for time series analysis. A PhD in Physics, Astronomy, or a closely related field is required. The position will entail work on a
-
network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or