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. The chosen candidate will collaborate with clinicians to drive impact from these models, and use them to benefit patient care. General Duties: Develop multi-modal statistical and machine learning methods
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interdisciplinary collaboration. Proficiency in programming is required. Excellent knowledge of oral and written English is a requirement. You are expected to be able to teach in English. Additional qualifications As
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collaborate closely with experimental partners (ICCF, IJL, IC2MP, and Syensqo) to validate computational predictions, ensuring the development of catalysts that are both highly active and stable under harsh
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. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model for diagnosis and prognosis of different sarcomas. He/she will develop and train
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neural population dynamics recorded by experimental partners - Collaborate with project partners - Participate in scientific activities of the team and scientific consortium - Study learning mechanisms and
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. This position is part of the DOE-BES initiative Integrated Scientific Agentic AI for Catalysis (ISAAC), a multi-facility collaboration integrating experimental measurements, simulations, and data science to
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observational studies using the James Webb Space Telescope (JWST). The successful candidate will work with Prof. Daniel Eisenstein and collaborators on the analysis and interpretation of JWST data, with
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position in machine learning (ML). This position offers a unique opportunity to conduct both basic and applied research in concert with collaborators working on diverse scientific and security problems
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collaboration with industry partners and SMEs. You have a track record of scientific publications in relevant venues. You are proficient in Python and relevant machine learning frameworks such as PyTorch
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision