1,037 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" Fellowship positions
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, alignment, evaluation). Design multi-MLLM collaboration methods (knowledge transfer/distillation, federated learning). Build efficient training/benchmark pipelines and report results with clear metrics. Apply
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successful candidate, you will: This project with Dr. Nagarajan Vaidehi involves developing and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in
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analysis, PDE-constrained optimization and optimal control, numerical analysis and scientific computing risk-averse and fractional models, digital twins and data-assimilating models, machine learning and
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Responsibilities: Conduct research in Systems Biology to study cell signaling Perform large-scale signaling analysis or protein-interactome analysis Utilize machine learning-based biological data mining and analysis
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Qualifications Experience with machine learning and AI models. Ability to communicate clearly with colleagues, Data presentations Scientific publication experience Special Instructions Priority Application Review
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research projects in computer vision, machine learning, AI, and robotics. Projects may include physically-grounded AI guidance agents, modeling of multimodal data, and generative AI systems for situated
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information/data from one structure can be used to manage similar structures from the same population. New machine learning, sensing and digital twin technologies will be developed with the aim of driving new
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Machine Learning (OxCSML) research group, with responsibility for leading and carrying out research pertinent to the project, as well as day-to-day management of research activities relevant to the project
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-disciplinary areas of artificial intelligence machine learning big data and data analytics software and security mobility and autonomy The Presidential Postdoctoral Fellowship is proudly supported by generous
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applications for a Postdoctoral Fellow with Professor Pragya Sur. Professor Sur’s lab focuses on research in high-dimensional statistics, machine learning theory, or more broadly, mathematical foundations of AI