72 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Lunds universitet
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Systems, Internet Systems and Computer Networks, Robotics, Machine Learning and AI, Automatic Control, or Mathematical Modelling and Optimization. Documented good profiency in software development. Good
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found here https://www.maxiv.lu.se/beamlines- accelerators/support-labs/microscopy-labs/ . This is a temporary position from March until October 2026. Qualifications for a successful candidate are: Hold
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electrochemistry Demonstrated ability to work independently Excellent command of the English language, good communication, and team working skills If not already proficient, be willing and able to learn X-ray
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teaching environment at the department. The main language of the PhD program is English. However, non-Swedish speaking students are expected to acquire basic skills in Swedish during the period of employment
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addition to conventional software, the scope includes engineering of AI enabled systems (primarily ML and LLM), and thus MLOps (Machine Learning Operations), datacentric AI, and legal and ethical aspects of AI
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. Where to apply Website https://lu.varbi.com/en/what:job/jobID:906273/type:job/where:39/apply:1 Requirements Research FieldMedical sciencesEducation LevelPhD or equivalent Research FieldMedical
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capture. Ability to work independently, as well as in a group. Valid Swedish driver´s license as we use car to drive to field localities Other merits Utbildning: University education in i biology (Master’s
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regular project meetings and collaborate closely with other members of the research group. Publish scientific articles, both independently and in collaboration with others. Teach up to 20% of your working
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such as the heart and nervous system, invariably with fatal consequences. The project will focus on probing the molecular factors underlying this instability (see for example https://www.nature.com/articles
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in Lund and be part of CREATE Health and Lund University's Cancer Center . Subject description The project aims to increase the understanding of the biology associated with response to CAR T-cell