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Field
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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First Stage Researcher (R1) Application Deadline 31 Mar 2026 - 21:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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Mar 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
. The PhD student will work with patient cohort to perform biomarker analyses and statistical modeling of clinical outcomes. In parallel, the student will contribute to the development and validation of novel
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of Contract Temporary 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 position within a Research Infrastructure? No
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Framework Programme? Not funded by a EU programme Reference Number CNS2023-145425 Is the Job related to staff position within a Research Infrastructure? No Offer Description Descifrando la vulnerabilidad
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of statistical analysis is required. Strong programming skills in Python, R and Linux-based software or similar languages and experience with modern machine learning and deep learning frameworks parallel computing
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/or mixed-methods; no parallel enrollment in another PhD programme; fluent English language skills are a must; knowledge of Bulgarian is an asset; no previous contractual links to the IPS at any point
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Research theme: Control Engineering, Robotics How to apply: https://uom.link/pgr-apply-2425 UK only This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will
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parallel, it produces new, high-resolution computer models of the warm Last Interglacial period. Finally, PAST creates new knowledge by synthesising these two approaches through advanced statistics. This PhD