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. The role will focus on developing machine learning and mathematical optimization solutions for electric vehicle fleet charging optimization under different constraints. Key Responsibilities: Formulate
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to £41,478 per annum. An exciting opportunity for an established researcher or a recently completed PhD researcher with experience in malacology, epidemiology, data mapping and/or schistosomiasis modelling and
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or Machine Learning). The master thesis must be included in the application. Documented proficiency in English, please see requirements below. Documentation of skills in English language Strong communication
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. Perform any other duties relevant to the research programme. Job Requirements: PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive
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relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning techniques, and
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by using explainable AI To develop generative AI techniques to design novel biologics for cancer Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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UiO/Anders Lien 15th August 2025 Languages English English English Postdoctoral Research Fellow in Machine Learning Apply for this job See advertisement About the position Position as Postdoctoral
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applies. 2 Fixed-term position available for up to 24 months. Flexible work arrangements can be negotiated with the right candidate. Be part of the Australian Institute for Machine Learning -- the largest
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Engineering, etc.), expertise in cutting-edge AI and machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role
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at the Institute of Genetics and Cancer. Informal enquiries may be directed to Dr Athina Spiliopoulou (A.Spiliopoulou@ed.ac.uk ). Your skills and attributes for success: PhD in machine learning, genetic epidemiology