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- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
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the duration of the fellowship. Qualification requirements Formal qualifications Education equivalent to five years at university level in Norway, with two years (120 credits) at Master’s level in a relevant
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organization of the fighting parties? More information about the project can be found here: https://www.sv.uio.no/isv/english/research/projects/wow/index.html The PhD Fellow is expected to develop a research
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analytics, and the use of machine learning for real-world evidence generation. Develop and apply innovative methods for analysing large-scale healthcare data, including advanced epidemiological, statistical
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guidance throughout the duration of the fellowship. Qualification requirements Formal qualifications Education equivalent to five years at university level in Norway, with two years (120 credits) at Master’s
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considering both decision objectives and available resources. The central scientific aim of the PhD project is to establish formal links between uncertainty representations, risk measures, and downstream
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production from the last five years. Experience with attracting external research funding and leading scientific research projects Experience with scientific programming and the use of numerical methods in
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possess the teaching/pedagogical qualifications that meet the requirements for an associate professorship (incl. formal training), the department shall facilitate the acquisition of such qualifications
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scientific frontier. Duties of the position Fundamental contributions in foundation models for underwater robotics. Focus on implementable methods for onboard robotic autonomy. Experimental deployments and
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. Integreat develops theories, methods, models, and algorithms that combine data with general or domain-specific knowledge, helping lay the foundations for the next generation of machine learning. Integreat
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artificial intelligence (AI) and an increasingly important force in a digital and data-driven world. Integreat develops theories, methods, models, and algorithms that combine data with general or domain