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Aarhus BSS Graduate School, Aarhus University invites applicants for two three-year PhD scholarships within the research project “Decoding Danish Firm Innovativeness from the Consumer Perspective
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dynamics of complex systems particle physics solid state physics theoretical physics X-ray physics For further information, please visit our website: http://www.uni-goettingen.de/en/488933.html Course
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First Stage Researcher (R1) Positions PhD Positions Application Deadline 5 Apr 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Is the job funded through the EU
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promising lean alloy system for additive manufacturing, as the mechanical properties can be tailored through phase composition, distribution and morphology by tuning process parameters. The work is carried
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/ProvinceThessalyCityLarissaPostal Code41500StreetViopolis CampusGeofield Contact State/Province Thessaly City Larissa Website http://www.bio.uth.gr/ Street Biopolis Postal Code 41500 E-Mail avoul@uth.gr Phone +302410565294 Mobile
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to exchange key radionuclides, which may lead to release or enhanced adsorption of 90Sr and 137Cs. Understanding the likely changes in both the solid and solution phases during this zeolite aging process are
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us and contribute to better health for all Where to apply Website https://kidoktorand.varbi.com/en/what:job/jobID:910639/type:job/where:39/apply:1 Requirements Research FieldMedical sciencesEducation
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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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touch with Ine van 't Land, Corporate Recruiter, via vacaturemeldingen.psg@wur.nl . Ready to apply? Click on the application button next to the vacancy on our website. Only applications submitted through
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, data science, applied mathematics, physics, materials science, or a related field. Solid background in machine learning and/or computer vision. Interest in representation learning, active learning