438 phd-computer-science-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at KINGS COLLEGE LONDON
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/senior lecturer to develop and lead an ambitious programme of research in the field of PET Physics, with expertise and interest in PET technology, methodology and data analysis. This will involve
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advancing our understanding of heart failure and accelerating the development of novel interventions. Applicants must hold a PhD in a biological sciences discipline and demonstrate substantial experience
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22 Aug 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Chemistry Engineering Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country
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affiliated with the Informatics Department in the Faculty of Natural, Mathematical and Engineering Sciences. This is a full time post (35 hours per week), and you will be offered a fixed term contract until 31
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research program dedicated to improving our understanding of ALS and informing future clinical trials. You'll also benefit from being part of a larger team investigating Treg biology and Treg-focused
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Application Deadline 9 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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the following skills and experience: Essential criteria: PhD in Neuroscience, Developmental Biology, Cell Biology, Genetics, or related field Proven postdoctoral research experience (minimum 3 years
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criteria PhD (or near completion) in bioinformatics, computational biology, machine learning, or a related field Significant experience in the analysis of cell- or imaging-based datasets, such as spatial
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27 Aug 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Political sciences Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country
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for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets