14 study-phd-engineering "https:" "UCL" Fellowship positions at Carnegie Mellon University
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curious to deliver work that matters, your journey starts here! Since its inception in 1905, the Carnegie Mellon Department of Chemical Engineering has been on the leading edge of research and innovation in
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-throughput microbiome analysis. Analyzing complex datasets derived from microbiome studies and microfluidic experiments. Collaborating with interdisciplinary teams, including microbiologists, engineers, and
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curious to deliver work that matters, your journey starts here! Since its inception in 1905, the Carnegie Mellon Department of Chemical Engineering has been on the leading edge of research and innovation in
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, Pennsylvania 15237, United States of America [map ] Subject Areas: Mathematics; Formal Methods; AI Appl Deadline: (posted 2026/01/15 05:00 AM UnitedKingdomTime, listed until 2026/07/16 04:59 AM UnitedKingdomTime
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of a specialized field, process, or discipline and may involve organizing and implementing complex research plans, the development of methods of research, testing and data collection, analysis and
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duties as assigned. REQUIREMENTS: REQUIRED: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong programming skills. Strong background in machine
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the study of science, mathematics, and philosophy of mathematical discovery. Our project has three main themes; ideal candidates will have an interest in one or more of these themes. Theme One: Proofs in
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project. This position will require an in depth knowledge of a specialized field, process, or discipline and may involve organizing and implementing complex research plans, the development of methods
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for someone who shares our values and who will support the mission of the university through their work. Qualifications PhD in Neuroscience, Cognitive Science or a related field Extensive experience algorithms
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. Qualifications: PhD required or must be obtained by start date Relevant experience might include: Working with large language models (fine-tuning, prompting, evaluation) Online/lab experiments on belief change and