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interpretation which will contribute to reports when required. You will develop, establish, and pursue appropriate analytical protocols and techniques to support research, including standardized protocols
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recognised expertise in environmental science and palaeoclimate research, contributing high-resolution environmental datasets and analytical capability to the project. The role will support the collection
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. This post is full-time and fixed term for two years with the potential to extend depending on further funding. The successful candidate will hold, or be close to completion of, a PhD/DPhil in economics or
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assessments What You’ll Need to Thrive You will be successful in this role if you bring: A PhD in Electrical Engineering, Mechanical Engineering, Data Science or a related discipline Proven experience with
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Infrastructure Computer Vision Data Analytics for the Built Environment You should possess: A completed PhD in a relevant discipline. Strong research expertise in digital engineering and built environment research
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to completion) in a biomedical, bioinformatic or relevant subject. You must have a strong bioinformatic, analytical and programming skills, applicable or multi-omic or spatial data. You need to have a strong
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strong bioinformatic, analytical and programming skills, applicable or multi-omic or spatial data. You need to have a strong interest in the research topic including renal pathology and to hold experience
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. The post holder provides guidance to less experienced members of the research group, including postdocs, research assistants, technicians, PhD, and project students. This full-time fixed-term post is funded
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data generated by super-resolution STED microscopy, FLIM, FRET and FCS. Candidates must hold a PhD in cell biology, biophysics or biochemistry along with experience in advance quantitative microscopy
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developing machine learning pipelines for imaging data. Excellent analytical, problem-solving and communication skills. The ability to work independently and collaboratively within a multidisciplinary research