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for part-time employment. Starting date: 27.03.2026 Job description:PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1 Commencement date
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be embedded within Moderna's Clinical and Quantitative Pharmacology (CQP) function and will contribute to key modeling and simulation deliverables for drug candidates across early and late stages
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members of our community have a responsibility to uphold these values. Application Materials Required: Further Info: http://www.bme.duke.edu https://www.bme.duke.edu
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characterization platform for innovative materials by combining advanced experimental techniques, physics-based mesoscopic modeling, and artificial intelligence. Within this context, high-throughput experiments and
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Postdoctoral Research Fellow position, focussing on mechanistic modelling of pharmaceutical processes. This role offers a unique opportunity to join a dynamic research team focused on advancing the understanding
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architecture, activation processes, and time-dependent dissipative phenomena [2]. This framework provides a relevant basis for developing models applicable to a wide range of functional soft materials (e.g
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itself by the use of materials, orientation and type of buildings, or the influence of vegetation. Project description The candidate will focus on the urban environment and develop a model to predict the
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characterization platform for innovative materials by combining advanced experimental techniques, physics-based mesoscopic modeling, and artificial intelligence. Within this context, high-throughput experiments and
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to data analysis, feature engineering, model development, evaluation, and documentation, while progressively gaining exposure to production systems, client-facing work, and modern AI practices across
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Coordinate contribution to modelling projects and platforms supporting reporting, communication andmeeting organization Where to apply Website https://jobs.helmholtz-hzi.de/job-invite/654/ Requirements