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openings available. Internal Number: 362548 Required Qualifications: * Ph.D. or Masters with equivalent experience in Computational Biology, Biostatistics, Bioinformatics, Computer Science, Data Science, or
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, the majority of whom are PhD candidates. This section works actively to foster an inclusive environment that promotes academic, professional and social networking. As a PhD candidate at OsloMet, you will have
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collegial respect and academic freedom tempered by responsibility. We develop talent by offering national/European and global networking opportunities, unique research infrastructures, and a collaborative
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of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading experts in machine learning for healthcare. You will also be affiliated to the School of Health
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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to focus on the relationship between geometry and quantum theory. A key objective will be the conceptual and mathematical understanding of the original Penrose spin network, with a view toward foundational
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collegial Department (29 faculty) that nucleates a larger interactive community (nearly 100 faculty). We support an exceptional Graduate Training Program, host two training grants, a robust weekly seminar
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supporting the clinical programme in all activities related to the in vitro production and preservation of equine embryos (ovum pick-up, oocyte maturation, intracytoplasmic sperm injection, IVF, embryo culture
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University/NL. The successful candidates commit to actively participate in networking including regular research visits to the partner laboratories. Requirements: university degree in chemistry or physics and
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular