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proficiency with at least one statistical programming language (R, SAS, Python, etc.). Strong record of scholarly productivity, including peer-reviewed publications. Excellent written and oral
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, sufficient programming fluency (e.g., Python; familiarity with common ML tooling) to run computational experiments, and excellent communication skills, including writing for publication and presenting results
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for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defense are eligible for appointment. Programming skills in GAMS and Python. Experience with HPC. Experience with
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to scientific problems, preferably with materials or polymer datasets. Proficiency in Python and scientific computing libraries; familiarity with machine-learning frameworks and data processing tools. Experience
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, Public Health, or a related health sciences discipline. Demonstrated experience with quantitative data analysis and proficiency with at least one statistical programming language (R, SAS, Python, etc
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, economics, or a closely related field. Excellent knowledge of computational linguistic tools and machine learning techniques. Experience with data analysis with Python and STATA. Prior experience in
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highly skilled Postdoctoral Fellow with a proven dual‑mode research profile capable of independently performing laboratory experiments and coding predictive AI models in Python to forecast biomaterial
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appointment). Strong background in statistical or machine learning methodology, optimization, or high-dimensional data analysis. Proficiency in R or Python; experience with deep learning, causal inference
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/Python). Familirarity with AI/ML methods for scientific computing and openness to explore different approaches Very good command of English is required (spoken and written) Additional Information Benefits
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the OpenQuake platform. The development will be carried out in a collaborative environment, using modern programming tools and languages aligned with the project's needs (e.g., Python and QGIS). 8 - Location