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Field
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of published research relevant to clinical medicine, especially those using quantitative research methodologies. Experience and demonstrated achievement in University-level teaching and learning. A record of
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, corresponding to pre-, intra-, and post-operative phases of brain surgery. The work includes data pre-processing, implementation and training of deep learning methods, and evaluation of the results. Legislation
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and qualifications: Experience in deep learning for remote sensing. Contracting requirements: Presentation of the academic qualifications and/or diplomas, if applicable. Enrolment in Master's degree in
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an excellent environment for deep innovation, out-of-the-box thinking, and creative problem solving. We will teach you what you do not yet know through mentoring, peer support, and many educational opportunities
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computational methods. A deep understanding of mass spectrometric, intact and sub-unit protein RPLC-MS analyses, bottom-up RPLC-MS/MS approaches, other protein structural analytical methods and techniques
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(deep learning) for subsurface studies (seismic interpre-tation). A part of the candidate’s job is to contribute to administrative work in the pro-ject and actively participate in communication with other
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work on the project together with Professor Ester Barinaga. We seek a candidate interested in developing this line of research with a deep interest and specialization in Complementary Currencies and
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000 individuals in UK. As part of a wider strategy to develop a deep human experimental medicines platform, this project aims to mainly focus on using novel human in vitro platforms using IBD gut stem
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community where different backgrounds, identities, and experiences are valued, and where our people are empowered to thrive through supportive leadership, shared responsibility, and a deep commitment to
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are expected to acquire basic pedagogical competency in the course of their fellowship period within the duty component of 25 %. Place of work is the Department of Informatics at Blindern, Oslo. Project