25 computational-physics "https:" "https:" "Universidade do Minho" PhD positions at Linköping University
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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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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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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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-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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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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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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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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, 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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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes