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applicants for a postdoctoral fellow position in the Laboratory of Systems Pharmacology (LSP; https://labsyspharm.org/ ), part of the Harvard Program in Therapeutic Science, at Harvard Medical School in Boston
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knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics
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include modeling of bulk and single-cell transcriptomic profiles, integrative multi-omics analysis, and the fusion of molecular data with clinical and imaging features. Organizational Status The successful
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days to express their opinion, in a preliminary hearing. Where to apply Website https://www.ipn.pt/bolsas Requirements Research FieldEngineering » Computer engineeringEducation LevelBachelor Degree
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 26-Nov-25 Location: Los Angeles, California Type: Full-time Categories: Academic/Faculty Medical Imaging Internal
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scientific computing, image data processing and numerical simulations would be most welcome You should enjoy working in an interdisciplinary, multinational research environment Being an enthusiastic researcher
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, including design approaches, scanning methods, signal processing techniques, and comparison with alternative detection technologies. ii. Support design and development of NQR prototype, including system
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, foundation models, multimodal data, and combine this with either modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image
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improvements. Validate reliability and scalability via thermal cycling/HTS/electrical stress on test vehicles; build prototype stacks (e.g., interposer/test-chip) to evidence manufacturability. Report and
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industry and international partners. For more details, please view https://www.ntu.edu.sg/atmri . We are looking for a Research Fellow to conduct research on air traffic management (ATM) algorithms and data