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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Computing Science seeks a postdoctoral researcher who will work on Compilers for Linear
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learning can improve software architecture recovery, how to optimize machine learning models at compile and runtime, and autonomous agents for software development. Part of the research is conducted through
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English and be compiled into a PDF-file containing: résumé/CV, including a list of publications, a general description of past research and future research interests (no more than two pages), contact
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. The applicant should have the ability to compile results into scientific publications, Furthermore, work with data management solutions/servers is required. Additional useful qualifications Since appointment as a
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on adaptive parallelism with OpenMP Research how to efficiently compile SYCL and OpenMP programs on RISC-V platforms Co-supervise PhD students Participate in the coordination of our activities in the DARE
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, SACO-S and OFR/S, dated 1st February 2022. Instructions on how to apply Applications shall be written in English and be compiled into a PDF-file containing: résumé/CV, including a list of publications, a
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written in English and be compiled into a PDF-file containing: résumé/CV, including a list of publications, a general description of past research and future research interests (no more than three pages
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Applications shall be written in English and be compiled into a PDF-file containing: a résumé/CV, including a list of publications, a general description of past research and future research interests
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Lund University, SACO-S and OFR/S, dated 1st February 2022. Instructions on how to apply Applications shall be written in English and be compiled into a PDF-file containing: a résumé/CV, including a list
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, temporary stay at companies in Stockholm to gain insight into the production of antigen / peptides and training in FluoroSpot technology, incubation and antigen stimulation of cells, result compilation, data