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dynamic research environment. Strong organizational skills and ability to manage multiple tasks and deadlines effectively. Adaptability and openness to learning new methodologies and techniques. Commitment
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the nominal length of study an attractive and good learning environment for PhD candidates The programme offers several courses and candidates from other programmes may apply for admission to the individual
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characteristics Be willing to acquire new knowledge quickly, and to use existing knowledge in new ways Be able to conduct independent activities and thinking, but also enjoy working in a teambased environment and
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learn how to do scientific research of high international standards, which shall lead to the award of a PhD degree. Second, you will produce results for the project you are working on. Tasks include
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, and entrepreneurship. Doctoral Candidates will gain transferable skills and learn from industry role models, equipping them to make significant contributions to solving the AMR crisis. The succsesssful
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methods to be considered for numerical optimization by an Energy and Emission Management System (EEMS). Data-driven AI methods (e.g. Reinforcement Learning and/or Recurrent Neural Networks) to be considered
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toward popular science dissemination Participate in international activities such as conferences and/or workshops Teach history subjects and/or computational methods to historians Required selection
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close relation with another PhD student in Université de Lille, France. The selected candidate will have the opportunity to learn form a consortium of 8 institutions (10 Beneficiaries, 3 Partner
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education corresponding to a cand.med.vet. degree, with a learning outcome corresponding to the descriptions in the Norwegian Qualification Framework, second cycle. The applicant must have a documented strong
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. The employment period is 3 years. If learning Norwegian (level A2 corresponding to at least 15 credits) is to be completed before the end of the employment period, the employment period can be extended by 10 weeks