153 machine-learning "https:" "https:" "https:" "https:" "https:" "The Francis Crick Institute" positions at Chalmers University of Technology
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Join us at the forefront of life science AI. We are looking for a postdoctoral researcher to develop cutting‑edge, multimodal transformer‑based deep learning methods to extract insight from genomic
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. Read more about working at Chalmers and our employee benefits . Learn more about life in Gothenburg and Sweden’s family-friendly policies, including generous parental leave, subsidized childcare, free
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Chalmers and Volvo Car Corporation. Who we are looking forThe following requirements are mandatory: a Master's degree (masterexamen) of 120 credits or a Master’s degree (magisterexamen) of 60 credits* in
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for documented circumstances such as parental leave or military service. You have demonstrated independent, high-quality research and show strong potential to build an internationally competitive research program
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to the seven-year eligibility limit may be made for documented circumstances such as parental leave or military service. You have demonstrated independent, high-quality research and show strong potential
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parental leave or military service. You have demonstrated independent, high-quality research and show strong potential to build an internationally competitive research program. We also expect you to have
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parental leave or military service. You have demonstrated independent, high-quality research and show strong potential to build an internationally competitive research program. We also expect you to have
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the application deadline. Exceptions to the seven-year eligibility limit may be made for documented circumstances such as parental leave or military service. You have demonstrated independent, high-quality research
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field, obtained within seven years before the application deadline. Exceptions to the seven-year eligibility limit may be made for documented circumstances such as parental leave or military service. You
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focus on technology foresight developing data-driven approaches for probabilistic modelling of new technologies; a second will focus on policy analysis leveraging machine-learning approaches