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Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired
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) Résumé or CV (3) Official or unofficial transcript (4) Analytic writing sample of 20 pages or less (5) Names and contact information for three references Materials must be submitted by April 15, 2026
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or CV (3) Official or unofficial transcript (4) Analytic writing sample of 20 pages or less (5) Names and contact information for three references Materials must be submitted by April 15, 2026, at 11:59pm
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transcript (4) Analytic writing sample of 20 pages or less (5) Names and contact information for three references Materials must be submitted by April 15, 2026, at 11:59pm Eastern. Applications will be
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. Assist with data collection and analysis to support governance processes and reporting. Participate in other various special projects as needed. Your general location of work will be in the CGPS offices
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field Proficiency in at least one programming language (Python, R, C++, Julia, …) Good analytical skills with a sound understanding of data evaluation Prior experience with single-cell data analysis
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Your Job: This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining
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laboratory activities in compliance with applicable regulations and protocols. Conducts literature searches and reviews, compiling information for journals and suggesting uses for new techniques to the P.I
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into the open-source CADET simulation framework, enabling fully predictive process simulations without extensive experimental calibration. Embedded in the Helmholtz Graduate School for Data Science in Life, Earth
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++, …) Experience in neuroscience is an advantage Good analytical skills with a sound understanding of data evaluation Good organisational skills and ability to work systematically, independently and collaboratively