312 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" research jobs in Sweden
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what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Location: Uppsala Form of employment: Temporary employment 24 months Scope: 100% Start date: By agreement (preferably spring
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located at SciLifeLab in Stockholm. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in
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. The primary objective is to develop computational methods, using deep learning–based protein design, for the successful design of 2D lattices. These methods will then be applied to generate designs targeted
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ecology and in ecosystem-based management. As a person, you are responsible and good at communicating. You enjoy working in a group and demonstrate capacity for learning new things, working systematically
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Postdoctoral Position and Postdoctoral Fellowship (2yrs) in Intracellular Host-Pathogen Interactions
proteomics analyses. APPLICATION PROCEDURE Please note that the application procedures differ between the two postdoc projects. More information about the application procedures is provided here: https
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Instructions on how to apply Applications shall be written in English and be compiled into a PDF-file containing: CV, including a list of publications, Where to apply Website https://lu.varbi.com/en/what:job
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is considered the official date of completion. Exceptions to the three-year eligibility limit may be made for documented circumstances such as parental leave, sick leave, or military service. What you
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that you will help us to build the sustainable companies and societies of the future. The research at the Division of Machine Elements is mainly focused on tribology and its applications. The research group
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clicking the button below. Union representatives: https://internt.slu.se/en/my-employment/employee-associations/kontaktpersoner-vid-rekrytering/ The Swedish University of Agricultural Sciences (SLU) has a
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will (micro-)benchmark Java-based applications using JMH. You will collect performance measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning