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materials, catalysis and/or surface science. For Topic 4, candidates must have documented skills within computational modelling of atomistic processes. Experience in scientific programming, e.g. using Python
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Collaboration with computational protein design partners and clinical reproductive biology collaborators Supervision of MSc and BSc students and contribution to publications You must have: A PhD degree in
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and tools. Experience in teaching advanced and fundamental science classes for university students. Experience in collaborations and bringing new ideas. As a formal qualification, you must hold a PhD
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of circumstances under which university scientific advice is given to private companies; A background within scientific computing, using tools such as R, Julia or Python; Knowledge of using data science in relation
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qualifications: As a formal qualification, you must have a master’s degree or PhD degree (or equivalent) in engineering or equivalent within the area of bioinformatics, computational biology, or a related field
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hardware accelerators, or quantum information science. Responsibilities and Qualifications Your primary responsibilities will be centered around the fabrication and characterization of TFLN/TFLT PICs
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PhD degree in Computer Science, Electrical Engineering or equivalent. Research interests and a scientific track record in Edge Computing research fields, such as Embedded AI, Edge AI, TinyML, and AIoT