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results but are hampered by large individual differences in response. It is evident that we need to rethink the premises of randomized controlled trials (RCTs) to better predict who will benefit from which
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experimentation, modelling, and noise‑control strategies across systems such as airfoils, ducted propellers, drones, and wind‑energy devices. With strong academic and industry partnerships, our group tackles
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to improve predictive models and inform design strategies. Work in Practical Settings — engage directly with NIHE to implement and test research methods in operational housing schemes. This work will equip
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variants as functional and assess their impact on gene expression. Contribute to large-scale modeling of engineered traits to predict performance and optimize design. Required Qualifications: PhD in
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Researcher for the Mechanical Systems Modeling (MSM) Group. The Electric Motor Researcher will conduct detailed analysis of electric motors and motor drive systems used in gas centrifuge applications
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, and clinical data. - Apply machine learning and foundational modeling to support predictive or exploratory analyses. - Collaborate with interdisciplinary teams to refine multi-modal pipelines
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posted here will be among the first ones to start in the centre. Please see the centre’s website: Future Aluminium Structures (FAST) - NTNU PhD Position 1: Modelling Plastic Flow and Fracture in Recycled
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, better adapted individuals can be selected at the seedling stage using only genetic data, accelerating the breeding cycle. Incorporating information about plasticity can aid genomic prediction modeling
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systems or smart buildings, such as regression, classification, time series analysis, or basic predictive modelling. Experience with data handling, including data cleaning, transformation, exploratory
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lightweight deep learning model for welding defect recognition. Weld. World. https://doi.org/10.1007/s40194-024-01759-9 J. Franke, F. Heinrich, R.T. Reisch, “Vision based process monitoring in wire arc additive