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be discussed. About you: To be successful in this role, we are looking for candidates to have the following skills and experience: Essential Criteria A PhD awarded (or near completion) in a relevant
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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researchers at Queen Mary University of London (Dr Margherita Malanchini) and King’s College London (Professor Robert Plomin), contributing to a broader network of PhD students and postdoctoral researchers. Key
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, quantitative and qualitative data analysis; and working with a network of European collaborators (the EuroWISE collective). Work Package 2 (Analysis and Data Management): The PDRA will be responsible for data
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understanding of infertility and placenta-related complications of pregnancy. Applicants must hold a PhD in cell, developmental or reproductive biology. Experience in human embryology and cell biology methods
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About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and
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The post holder will be expected to have a PhD in law or political science and skills to handle large dataset and conduct quantitative analysis and other empirical analysis. Familiarity with LLM (large
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into human biology and may in the future lead to improved understanding of infertility and placenta-related complications of pregnancy. Applicants must hold a PhD in cell, developmental or reproductive biology
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—an ambitious, EPSRC-funded initiative led by Dr. Sina Sareh, Academic Leader in Robotics. We are looking for a highly skilled researcher with expertise in robotics, AI, software engineering, or computer science
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following skills and experience: Essential criteria A PhD in Cell or Molecular Biology, Immunology or a related subject * Experience of mammalian cell culture (both primary and cell lines) Excellent knowledge