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doctoral degree in Computer Science or Biomedical Informatics or a closely related quantitative field. The successful candidate demonstrates documented expertise in machine learning and distributed
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, Data Science, Machine Learning, or a closely related field. Strong programming skills in Python or MATLAB. Very good communication skills in English, both written and spoken, since the research
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optimization or machine learning methods relevant to materials research. 4/2/2026
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., computational learning theory, expressiveness of transformers and other models, xAI, formal methods) or equivalent; willingness to conduct research on artificial intelligence/machine learning, combined with
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structure calculations, vibronic property simulations, and analyzing surface adsorption phenomena. Knowledge of machine learning potentials (e.g., GAP, ACE) or reactive force fields is a plus, as fallback
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and acquire spectral data Perform Raman spectral data analysis using machine learning algorithms Work with DiSTAP plant biology collaborators, training researchers in spectrosocpy Work with local
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towards improving controllers in turbulent flows. On any given day, you may be called on to: Own and execute novel machine-learning workflows related to wind conditions and control performance. Post-process
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senior research position to work on projects related to computational analysis of mass spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational
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interaction, or design. This eligibility requirement must be met no later than the time the employment decision is made. It is commendable if you have experience designing for the body, or in using soma design
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data science, and/or public health or related fields including health services research, health informatics, computer scienceExperience in data analysis using statistical software & machine learning (e.g