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–functional modeling of root system architecture. Phenomics data integration and high-dimensional trait analysis. Predictive breeding and quantitative genetic modeling. Machine learning approaches to genotype
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anticipated that the successful applicant will pursue advanced doctoral training (MD, PhD or MD/PhD) subsequent to this position. Set up, adjust, calibrate, clean, maintain and troubleshoot equipment Clean
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and take ownership of work Interest in AI, machine learning, image/audio processing Where to apply Website https://www.timeshighereducation.com/unijobs/listing/408369/research-engineer-r… Requirements
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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Automatization and Digital Enhancement of Characterisation Techniques: Joining the Dots between AI, Machine Learning and Materials Advances School of Chemical, Materials and Biological Engineering
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. A long-term attachment (6-12 months) and
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methodologically strong and motivated to work at the intersection of applied machine learning, social sciences, and natural sciences. Essential qualifications: A completed PhD in data science, computer
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23 Feb 2026 Job Information Organisation/Company Instituto Politécnico de Setúbal Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions PhD
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an MD or PhD in Biochemistry, Neuroscience, Microbiology, Immunology, Genetics/Genomics, Biomedical Sciences, Biology, or a related field of study from an accredited institution or a terminal degree in