26 cloud-computing-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "St" "St" "St" "St" PhD scholarships at Linköping University in Sweden
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- 12:00 (UTC) Country Sweden Type of Contract To be defined Job Status Full-time Hours Per Week 40 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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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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for tomorrow´s Swedish forest value chain. More information about WWSC can be found here: Home - WWSC The employment When taking up the post, you will be admitted to the program for doctoral studies. More
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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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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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to the program for doctoral studies. More information about the doctoral studies at each faculty is available at Doctoral studies at Linköping University The employment has a duration of normally four years’ full
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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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, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on methods that reduce compute, energy
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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