23 phd-position-in-data-modeling Postdoctoral positions at KINGS COLLEGE LONDON in United Kingdom
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document will provide information of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are
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26 Sep 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Biological sciences Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country
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27 Sep 2025 Job Information Organisation/Company KINGS COLLEGE LONDON Research Field Biological sciences Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country
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the PI — to interrogate ALS pathogenesis at an unprecedented level of resolution. By simultaneously analysing multiple data sets (MANT-ATP, methylome, transcriptome and proteome) derived from the same
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experimental assessments across the UK. The successful applicant will oversee data collection, management and analysis, and lead the dissemination of findings to academic and lay audiences. You will work closely
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the Centre for Research Staff Development for more information. About you: To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD
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oversee data collection, management and analysis, and lead the dissemination of findings to academic and lay audiences. You will work closely with families, NHS Trusts and charity partners, and contribute
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Is the Job related to staff position within a Research Infrastructure? No Offer Description About us The Social Computation and Representation Lab (SoCR Lab; www.socrlab.net ) uses mathematical models
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, or related disciplines. Previous experience in social cognitive research Knowledge and prior experience of model simulation, recovery, and fitting of decision-making data Excellent verbal and written
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Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate