201 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" Fellowship research jobs at University of Oslo
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methodologies Experience with machine learning techniques Experience with pipeline development and testing (gitlab, simulated light curves…) Ability to work independently and to collaborate in an international
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conducting quantitative analyses or master game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement
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for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest
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four years are expected to acquire basic pedagogical competency in the course of their fellowship period within the duty component of 25 %. Place of work is Department of Chemistry at Blindern/Gaustad
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. Qualification requirements A PhD degree within neuroscience, psychology, medicine, machine learning or biology or equivalent. Doctoral dissertation must be submitted for evaluation by the closing date
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design and in silico validation intimately connected to experimental validation. In this project, you will develop machine learning methods and apply them in an interdisciplinary environment spanning
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at the University of Oslo. Postdoctoral fellows who are appointed for a period of four years are expected to acquire basic pedagogical competency in the course of their fellowship period within the duty component of
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills The candidate’s research proposal must be closely connected to the call and the research
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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The appointment is a full-time position and is made for a period of three years