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for observational studies Experience with machine learning techniques for patient-level prediction Prior experience working in distributed or federated data networks Familiarity with open-source research ecosystems
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. Chan, “When edge meets learning: Adaptive control for resource- constrained distributed machine learning,” in IEEE INFOCOM 2018- IEEE conference on computer communications. IEEE, 2018, pp. 63– 71. [3] G
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must be obtained prior to the start of employment. PREFERRED QUALIFICATIONS Experience with big data tools, ETL processes and machine learning programs or cloud platforms is preferred. COMMITMENT
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of machine learning to the practical tools of deep learning, now available through modern foundation models. For the theory part, the selected candidate will work in close collaboration with
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. ETRO, the Department of Electronics and Informatics (http://www.etrovub.be/) of the Vrije Universiteit Brussel (VUB), performs fundamental and applied research in signal processing, AI, computer vision
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expertise spanning the full breadth of operations research, including large-scale optimization, applied statistics, military logistics, warfare analysis, and critical infrastructure resilience. Our students
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on the career stage), in any area of psychology. In line with our strategic priorities, we are particularly keen to appoint colleagues with strong statistical expertise (big data, longitudinal
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SciLifeLab community both locally in Uppsala and in Sweden at large. For information about the SciLifeLab fellow program, see https://www.scilifelab.se/research/#fellows . SciLifeLab Fellows are also part of a
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following areas: AI and machine learning, natural language processing, large language models (LLM), experience in designing prompts, fine-tuning LLMs, or distributed systems. Good knowledge in one or more of
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data at an internationally competitive level. Experience of biostatistics or machine learning approaches Proficiency in a scripting language like R or Python, as well as ability to work efficiently in a