631 machine-learning "https:" "https:" "https:" "https:" "https:" "The Francis Crick Institute" positions in Norway
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within sanctioned boundaries. Underpinning both is the need for dependability models that, combined with telemetry-driven learning, can guide self-healing decisions in a way that reduces downtime without
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest in creative or artistic applications. Documentary evidence would be beneficial
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are also affiliated with the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) . The candidate is expected to join Integreat and strengthen the interdisciplinary research on the boundaries
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outcomes and economic performance, specifically addressing challenges such as overdiagnosis in cancer care. We will utilize economic theory, simulation, economic evaluation and machine learning to quantify
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(predictive) modelling, for example machine learning approaches. Experience in conducting field work in polar or alpine regions. Strong and preferably demonstrated interest in interdisciplinary work at the
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limited to these topics, but preference can be given to candidates with a potential to contribute to the ongoing academic dialogue in the department. Applicants must be able to teach in Norwegian or a
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, corporations and the international order; on the development of political and military strategy; on how the wars were prepared, experienced and remembered; and on how peace was made. BLOCKADE sets out to prove
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solutions that are practically viable. The successful PhD candidate is expected to carry out research on one or more of the following focus areas: Developing and training robust machine learning surrogates
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conducting quantitative analyses or master game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement
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while offering flexibility to tailor your training to specific needs and interests through elective courses and secondments. • Blended Learning Approach: Our training combines intensive in-person