25 computational-physics "https:" "https:" "https:" "https:" "Chalmers" scholarships at Linköping University
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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-assisted AI and control systems is to deliver the right and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you
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application! We are looking for a PhD student in Statistics and Machine Learning Your work assignments We are looking for a PhD candidate to work in the intersection of computational statistics and machine
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17 Mar 2026 Job Information Organisation/Company Linköping University Research Field Computer science Researcher Profile First Stage Researcher (R1) Application Deadline 13 Apr 2026 - 12:00 (UTC
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postgraduate education within Medical Science. The employment When taking up the post, you will be admitted to the program for doctoral studies. In connection with your admission to the doctoral program, your
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/tensions between the global North and global South. We will also consider applicants focused primarily on Swedish/Nordic cases or topics. For full information of the five REMESO research streams see: https
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, computer science, mathematics, statistics, physics, or a related area that is considered relevant for the research topic of the project, or completed courses with a minimum of 240 credits, at least 60 of which must
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level in machine learning, computer science, mathematics, statistics, physics, or a related area that is considered relevant for the research topic of the project, or completed courses with a minimum of
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, genetic manipulations, analysis of genomic rearrangements, telomere assays, and RNA sequencing. The activities include literature review, lab working and computational bioinformatics analysis. Your
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induction. You will combine advanced genetic engineering approaches with survival assays, fluorescence-based techniques in fixed and live cells, single-cell sequencing, and computational bioinformatics