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Field
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is
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of the position. Equivalent research experience will also be considered. You should have familiarity in handling large and complex datasets and skilled in programming languages such as R or Python. The ideal
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/ physics/ meteorology/ engineering/ biology. Experience in a computer programming language (e.g. Fortran, Python). A general understanding of the importance of the scientific method is essential. A previous
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to address the problem is to recruit a high performing PhD student to embark on a psycho-biological, mixed-methods programme of research that has the following aim: Develop a feasible, acceptable, efficacious
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applications are made at http://www.bris.ac.uk/pg-howtoapply . Please select PhD in Computer Science on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and
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supervised by Prof. Peter Scott, Director of the Lincoln Theological Institute. Tenable period The award is tenable for 3.5 years from September 2025- covering the full PhD programme in PhD Religions and
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Specified use +4 - covering a full postgraduate research programme Please note that existing postgraduate research students cannot be considered for this funding. Tenable period 4 years full-time or 8 years
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applicants who can confirm residency in the UK for at least three years before October 2025, you may also be eligible for a full award. If English is not the candidate’s first language, they must provide
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applicants who can confirm residency in the UK for at least three years before October 2025, you may also be eligible for a full award. If English is not the candidate’s first language, they must provide
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but not mandatory). A strong interest in materials simulation, quantum materials, and condensed matter physics. Experience with Python. Fluency in English is required. Finnish language is not required