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Field
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new algorithms for focused research questions in bulk and single cell tumor analysis, integrate tools and databases into existing high-throughput pipelines, and drive projects to completion and
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modeling and AI. This position will include: Developing new Generative AI algorithms for developing intelligent agents in areas such as planning, exploration, perception, physical reasoning, and memory
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ecology, remote sensing, and computer science. UAV imagery and increasingly sophisticated and targeted AI algorithms can estimate forage quality, biodiversity, and the abundance of individual plant species
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international collaborators. The group's interests cover a wide range of areas including extremal and probabilistic combinatorics, combinatorial optimization, graph theory, game theory, algorithmics and geometry
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, Algorithms, and Data" team at L2IT. Application procedure: Interested candidates must send: 1. A cover letter presenting their research project and their interest in joining the group 2. A Curriculum Vitae 3
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include the porting of lattice QCD libraries to the Exascale Architectures (e.g. Frontier at OLCF) and/or emerging programming models (HIP, SYCL, Kokkos, etc), software optimization and/or algorithmic
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computational methods and tools, including prior experience with algorithms relevant to computational biology, is a plus. ● Ability to work independently as well as part of an interdisciplinary team in a
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
, scientific computation, scientific software and algorithm development, and data analysis; demonstrated ability to conduct original, high-quality research in computational fluid dynamics and/or computational
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will also investigate process optimisation algorithms, providing a route toward autonomous optimisation and ultimately enabling long term stable operation under variable load conditions. This post is
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Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning