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Fusion Tribrid MS and Waters Q-ToF instruments are highly desired. Experience handling and analyzing large-scale MS, MS(MS) and/or proteomics-like datasets using statistical and machine learning techniques
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your machine learning expertise to cutting-edge automated optimisation challenges? We are seeking a Research Fellow in Digital Chemistry and Engineering to combine self-optimising flow reactor technology
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computational statistics, statistical machine learning, simulation and statistical programming). The postholders will join the dynamic and collaborative Department of Statistics. The Department carries out world
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aquaculture (e.g., behavioral analysis, growth prediction, digital twin, computer vision.) Develop, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets
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disciplines) Strong experience or demonstrated interest in AI, NLP, machine learning, or digital health research Experience working with clinical, communication, or patient-generated datasets is an asset
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are also affiliated with the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) . The candidate is expected to join Integreat and strengthen the interdisciplinary research on the boundaries
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, color, religion, sex, age, national origin, disability, marital status, sexual orientation, military/veteran status, gender identity, or other non-merit factors. If accommodations are needed
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Pay Grade/Pay Range: Minimum: $53,500 - Midpoint: $66,900 (Salaried E8) Department/Organization: 214251 - Electrical and Computer Eng Normal Work Schedule: Monday - Friday 8:00am to 5:00pm Job
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest in creative or artistic applications. Documentary evidence would be beneficial
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plants. The participant will learn and use multiple molecular biology, synthetic biology and plant biotechnology related tools and techniques including plasmid vector design and assembly, plant genetic