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project experience is acceptable. Experience with Hail, SQL or relational databases, Git/version control, cloud-based genomic analysis, PRS, Mendelian randomization, gene-environment interaction analysis
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system integration A record of peer-reviewed publications Experience with AI/ML-based control, such as reinforcement learning, learned or model-predictive control, or vision-guided manipulation Experience
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be expected to model prototypes of the fiber optic based sensors using standard Multiphysics software, perform out-of pile laboratory testing of the instruments in representative environments, and
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Science (DIHDS) and the Media and Innovation Laboratory (The MIL). The Manager applies advanced analytics, artificial intelligence, machine learning, predictive modeling, and related data-driven
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with colleagues. Who we are The Group of Integrated Photonics at Aarhus University studies how light can be generated and controlled on chips. Our work combines modelling, nonlinear optics, device design
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coding skills in Python with PyTorch, including reinforcement learning, imitation learning, and flow matching/diffusion-based generative models. • Experience designing hierarchical control
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of dissipation in magnonic systems. Develop theoretical models to describe and optimize the control of magnon dissipation via feedback. Collaborate with the experimental team to validate these models and propose
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teaching. Familiarity with state-space modeling, analysis of control stability and other advanced control topics. Demonstrated knowledge of spoken and written English. Strong problem-solving skills and
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the interactions between crop growth and environmental factors, and develop geospatial information-based models for environmental effects. Support the development of multidimensional “genotype–environment–phenotype
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to an early economic evaluation of wastewater-based epidemiology (WBE) systems to support existing surveillance and control strategies for norovirus in health and social care settings, funded by Health and Care