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foundations, focusing on the structure and complexity of quantum computational models; (ii) optimization and related graph-theoretic methods, using polyhedral geometry and algorithmic optimization (e.g., vertex
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energy deposition technology and accelerating its practical adoption in construction and beyond. The Research Fellow is expected to: • Assist the design and lead the commissioning and operation of
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microscopy, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand
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should have an aptitude for semi-independent laboratory work, which is well supported by the dynamic academic structure of the department. The candidate will also have the opportunity to work with
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data scientists, software engineers, biomedical researchers, and clinicians. Your research will focus on developing AI- and LLM-enabled methods and tools to structure, harmonise, and analyse clinical
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single cells make decisions during differentiation, in particular during development. Building on Bonsai, a Bayesian framework that leverages tree structures for distortion-free exploratory analysis
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 month ago
, pricing strategies, customer engagement, reputation, and long-term sustainability outcomes. The RA will contribute to empirical data collection, data cleaning, coding, database construction, and preliminary
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range from cell biological over biochemical to molecular biology and bioinformatics approaches. Collaborations with structural biologists are possible. Your profile Applicants should hold a PhD in
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-training, post-training and reinforcement learning for Large Language Models (LLMs); (c) lead the pre-training of both Dense and MoE LLMs, optimising for performance, scalability, model structure and
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technologies. You will join an interdisciplinary research environment focused on the structural and chemical characterisation of fibre‑based materials under operational conditions. The role requires onsite work