27 data-"https:" "https:" "https:" "https:" "https:" "https:" "Dr" uni jobs in Sweden
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FieldMathematicsYears of Research Experience1 - 4 Additional Information Website for additional job details https://academicpositions.com Work Location(s) Number of offers available1Company/InstituteChalmers University
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Information Website for additional job details https://academicpositions.com Work Location(s) Number of offers available1Company/InstituteChalmers University of TechnologyCountrySwedenCityGothenburgPostal
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Additional Information Website for additional job details https://academicpositions.com Work Location(s) Number of offers available1Company/InstituteChalmers University
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Computer ScienceCountrySwedenCityStockholmPostal Code10044StreetBrinellvägen 8Geofield Contact City Stockholm Website https://www.kth.se/en Street Brinellvägen 8 E-Mail info@kth.se Phone 087906000 STATUS
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FieldMathematicsYears of Research Experience1 - 4 Additional Information Website for additional job details https://academicpositions.com Work Location(s) Number of offers available1Company/InstituteChalmers University
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Join the Computing Disease Evolution in Cancer (CODEc) group, led by Dr Eszter Lakatos within the Division of Applied Mathematics and Statistics and persue exciting research. As a Doctoral student
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in a wide range of biochemical and biophysical methods and offers a creative and strong research environment with excellent infrastructure (see https://www.cmps.lu.se for more information). The
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to apply Website https://lu.varbi.com/en/what:job/jobID:882724/type:job/where:39/apply:1 Requirements Additional Information Work Location(s) Number of offers available1Company/InstituteLunds
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Research FieldMathematicsYears of Research Experience1 - 4 Additional Information Website for additional job details https://academicpositions.com Work Location(s) Number of offers available1Company
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of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods