41 distributed-algorithm-"Newcastle-University"-"Newcastle-University" positions at Harvard University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Details Title Postdoctoral Fellow in Forecasting Species Distributions of Medicinal Plants School Faculty of Arts and Sciences Department/Area Organismic and Evolutionary Biology Position
-
well as the heterogeneity of cell states and their spatial distribution within a tumor. CyCIF is applied to tissues from a diverse set of sources, including genetically engineered mice, patient-derived xenografts propagated
-
research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins
-
-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
-
models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization
-
learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
-
, generative AI, NLP, or algorithmic decision systems Ideal applicants will have a strong background in operations research, statistics, or computer sciences and the ability to work across disciplinary
-
design and reinforcement learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools
-
learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
-
and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees