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to create interactive learning experiences. Career Readiness Competencies Take initiative to learn new tools, systems, or procedures on the job. Present ideas or updates in a clear and organized manner. Ask
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Knowledge, Skills, and Abilities: Hands-on experience performing FEFF calculations and data preprocessing for machine learning applications. Practical experience developing and training models using PyTorch
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tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/phd-position-computer-simulati… Requirements Research FieldEngineeringYears of Research Experience1 - 4 Research
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and machine learning. Knowledge of the basics of federated learning and causal inference is highly encouraged. Proven track record in research and development of machine learning algorithms. Proficiency
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for 10-12 weeks. Responsibilities: Collect and organize different datasets. Derive summary statistics of those datasets. Help with the implementation of machine learning models. Conduct literature
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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process systems engineering. The position aims to advance physically consistent and predictive thermodynamic modeling, including the integration of advanced machine learning methods, to support process and
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-making systems. Develop Advanced ML/AI Models for Air Quality Applications Applies machine learning (ML) and artificial intelligence (AI) techniques to enhance traditional chemical transport modeling
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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knowledge of process systems engineering. The position aims to advance physically consistent and predictive thermodynamic modeling, including the integration of advanced machine learning methods, to support