109 programming-"https:"-"https:"-"https:"-"CNR-IRIB-PALERMO" PhD positions in Norway
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clinical risk factors? 4. How can prediction models be validated to ensure they are trustworthy and reliable for integration into living digital decision aids at the point of care? About the PhD program The
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for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Program. Good oral and written presentation skills in English. You need strong skills in mathematics
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Admission to this PhD programme is continuous. To apply you need a five-year master's degree or equivalent in teacher education or other qualifications in teaching education, educational sciences
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contributing to the broader goal of building ethically aware and socially responsible language technologies. The candidate will submit a PhD plan within 3 months after the start of the PhD. Qualifications and
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meet the requirements for admission to the faculty's Doctoral Program Good oral and written presentation skills in English. You need strong skills in mathematics, probabilities, optimization and
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This PhD programme is multidisciplinary and cross-disciplinary building on applied mathematics and physics, technology and engineering—and the interplay between these. The programme has an applied
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approved PhD program. The successful candidates are expected to start on 1st September 2026. Qualification requirements and personal skills Applicants must hold a Bachelor’s and a Master’s degree or
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relevant Engineering discipline, or a related field. Foreign degrees must correspond with the admission criteria for the PhD program. Candidates submitting MSc thesis within 30. June 2026 may be considered
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-year Norwegian degree program, where 120 credits are obtained at master's level. Master's students can apply, but the master's degree must be obtained and documented before starting the position. You
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to MINA’s PhD programme. The documentation that is necessary to ensure that the admission requirements are met, must be uploaded as an attachment. Main tasks Develop machine learning models to produce forest