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Field
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training, travel to communicate findings, and professional networking will also be available. Learning Objectives: Under the guidance of a mentor, you will have the opportunity to learn to: (a) plan, execute
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an impressive and well-rounded profile. The post will be 24 months in the first instance, whilst a renewal of the contract is possible. About You You should have a PhD (or close to completion) in the area of
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, while also being part of the vibrant TIAS research community. Who we are looking for Postdoctoral Fellow is defined as being within five (5) years of applicants having passed their PhD. Applicants must
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conferences and/or research stays at foreign educational institutions Supervision of students and contribute to relevant teaching activities Mentoring PhD students, helping them with their research projects
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have submitted their PhD thesis. Applications within three years of obtaining a doctorate will be considered. In duly justified cases, applications falling outside this criterium may also be considered
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completed a PhD in engineering or computer science, or an equivalent foreign doctoral degree recognised as comparable to a Norwegian PhD. Competence in developing and applying machine learning methods Good
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/national programs, academic institutions, and research consortiums. Learning Objectives: Under the guidance of a mentor, you will have the opportunity to learn to: (a) plan, execute, analyze, and communicate
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towards better understanding what replication can mean for qualitative research. Last but most topically, the theme of replication raises a host of questions in relation to machine learning and artificial
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, including lectures and practical classes on the adaptation of forest ecosystems to climate change, with a focus on ecophysiology. Supervising doctoral dissertations (PhD students). Workload: 1.0 Where
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mapping database delivered to consortium members. Mentor graduate and undergraduate student researchers. Required Qualifications PhD in resource or environmental economics, economics, energy systems