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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental design
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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning
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minimum 5 years’ experience in epidemiology, data management, programming and statistics at supervisory level. Proficiency in SQL, Python/R, or similar tools; experience with big data platforms , machine
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Data Scientist (Artificial Intelligence). We now invite applications for the captioned post. Duties and Responsibilities Develop and apply advanced artificial intelligence and machine learning models
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: Prior experience running behavioral experiments is desirable, as is previous collaboration or engagement with researchers in economics. Familiarity with methods from machine learning will be a plus. All
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 13 days ago
acquisition Good communication skills in English and ability to collaborate in interdisciplinary teams Desirable qualifications Experience with machine learning methods for regression or signal interpretation
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. Emphasis is placed on artificial intelligence/machine learning approaches applied to digital data and multi-omics data. Additional responsibilities include mentoring students, collaborating with faculty
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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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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal