33 lecturer-in-computer-science PhD positions at University of Cambridge in United Kingdom
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Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
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-level degree in Mathematics or Computer Science with an orientation towards Theoretical Computer Science. A strong background in logic and complexity theory is highly desirable and the candidate must
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duties involve supporting computational infrastructure, coordinating with wider spectroscopic project teams and external science users, contributing to documentation and user manuals, and collaborating
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Fixed-term: The funds for this post are available for 1 year. Applications are invited for a Research Associate (Postdoc) to join the Prorok Lab in the Department of Computer Science and Technology
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well as to initiate new queries. As a member of an interdisciplinary team, the candidate will have the opportunity to receive training in a variety of techniques, including molecular biology, embryology, imaging
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cycles and refine deliverables accordingly. The skills, qualifications and experience required to perform the role are: A PhD in Computer Science, Civil Engineering, Data Science, Information Systems, or a
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and an interest in and familiarity with computational protein engineering approaches is essential. Hands-on experience in computational protein design and engineering is desirable. The ability to work
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of researchers who conduct cutting-edge research into NLP and AI within the University of Cambridge. Education: An excellent first degree in computer science, engineering or a closely related field Skills and
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Natural Language Processing (NLP) in the areas of culturally aware NLP or multilingual conversational NLP, and integration of such methods to support language technology in multiple languages
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward