34 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at University of Copenhagen
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. Employment and enrolment conditions follow the agreement between the Danish Ministry of Taxation and the Danish Confederation of Professional Associations (AC). More information on the PhD programme: https
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– is Denmark's largest science research and education institution with 4,000 employees and 9,700 Bachelor and master students in 12 departments. The faculty has an annual budget of DKK 3 billion. Learn
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. An individual career development plan containing research and transferable courses, international research visits, mentoring and career activities, is also a central element. Please visit https://www.interact
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addition to the specialised facilities and resources within reNEW and BMI, reNEW researchers have access to the core facilities at the other reNEW nodes as well as at the Faculty of Health and Medical Sciences: https
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to analyse and interpret complex data. ability to work independently and take initiative, good hands-on problem-solving skills, and the capacity to acquire new skills. We know that research shows that women
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interdisciplinary approach combines research in genetics, physiology and pharmacology, to better understand the complex interplay of the many factors that drive cardiometabolic disease. You can learn more in the
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on their assessment. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ . Interviews with selected candidates are expected to be held in February 2026 Questions
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departments. The faculty has an annual budget of DKK 3 billion. Learn more about The Faculty of Science at www.science.ku.dk You can read about the recruitment process at https://employment.ku.dk/faculty
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. Learn more about The Faculty of Science at www.science.ku.dk You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ .
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Develop machine learning interface for Daisy to improve support for data-driven process modeling We expect You Hold a master’s degree in computer science, preferably a PhD with postdoc experience