625 machine-learning "https:" "https:" "https:" "https:" "https:" "Dana Farber Cancer Institute" positions in Norway
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areas: Developing and training robust machine learning surrogates to replace computationally expensive high-fidelity simulations, enabling exploration of vast design spaces. Formulating optimization
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processes based on mobile digital technologies increase, so do the amount and severity of cyber threats. Both defenders and attackers are now using Machine Learning (ML) and Artificial Intelligence (AI
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Experience with AI / probabilistic AI / Machine Learning Experience with numerical optimization and MPC Strong programming skills (Python, C) Experience with predictive maintenance, fatigue, fault detection
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with the EU). For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/296940/post-doctoral-fellowship-norcie-norwegian-centre-for-international-economics Where to apply
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interests through elective courses and secondments. • Blended Learning Approach: Our training combines intensive in-person workshops at partner institutions with regular interactive online seminars, journal
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the department’s broader teaching portfolio. More information about the department’s academic profile can be found on https://www.ntnu.edu/ihf . You will report to the Head of Department. Duties of the position
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collaboration with world-leading international collaborators at institutions such as Netherlands Cancer Institute and Karolinska Institutet. For more information and how to apply: https://www.jobbnorge.no/en
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of experts? Then this job may be for you. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/296128/phd-fellowship-in-systems-neuroscience Where to apply Website https
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depend on the candidate’s qualifications and CREATE's needs. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/295895/phd-research-fellow-in-social-sciences Where
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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable