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1st August 2026 Languages English English English The Department of Energy and Process Engineering has a vacancy for a PhD Candidate in Plastics Pollution Modelling and Life Cycle Assessment Apply
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missing and incomplete symptom data can introduce bias and worsen existing inequalities. This PhD will develop innovative statistical and machine learning approaches to understand, model, and overcome
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learn new things - A strong programmer who’s comfortable with Python - An open-minded thinker and precise communicator who enjoys collaborating with colleagues from a wide range of backgrounds and areas
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computational fluid dynamics. • Experience in modeling, uncertainty quantification, or statistical methods. • Experience in data science or machine learning is considered an asset. • Experience with high
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driving simulation, human-machine interaction, physiological and behavioral data collection, AI-enabled systems, and translational safety research across transportation, public health, and national security
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with eight (8) years of experience; OR MS in the same fields with five (5) years
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
engineering Experiences in sensors and instrumentation Languages : A good level of English, written and spoken, is required Relational skills : Ability to work in a team and will to participate in the research
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years
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levels. Apply a strong understanding of enterprise cybersecurity and technology security challenges. Utilize knowledge of computer network defense tools and processes, including leading commercial vendor
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-NorthWind webpage for more details): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer