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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
endowment in excess of $3.9 billion. Job Description Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI Boston College, Department of Computer Science Salary Range: $66,000–$75,813
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
endowment in excess of $3.9 billion. Job Description Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI Boston College, Department of Computer Science Salary Range: $66,000–$75,813
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
for extension based on mutual interest. We are looking for individuals with a strong theoretical and practical background in large language models, machine learning, and natural language processing, combined with
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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
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vision and novel applications of machine learning. Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL dialect is preferred. Apply online at https
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@nki.nl . The closing date is November 21st 2025. Where to apply Website https://www.werkenbijavl.nl/vacatures/postdoctoral-research-fellow/ Requirements Research FieldMedical sciencesEducation LevelPhD
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publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential. Additionally, the candidate should possess an excellent
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, postdoctoral fellow¿s interests, and FIU CAPS¿ needs. Supervision Supervision of the postdoctoral fellow is based on a developmental approach to learning. Educational goals are individualized to integrate
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wireless communications, RF signal processing, and/or applied machine learning Strong background in digital communications and RF signal processing, ideally with experience in SATCOM, NTNs, or space-borne
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experimental design. Proficiency with machine vision and deep learning techniques, including image segmentation, landmark placement and metric learning, for the automation of phenotypic analysis of large image