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. This includes exploring the use of digital twins for bioreactors and deploying AI driven predictive models to improve optimisation, consistency and overall yield. The main focus for this role is to work with the
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, version control) and numerical workflows. Experience programming for data analysis and model workflows (e.g., Python, MATLAB; FORTRAN/C familiarity for model configuration). Demonstrated verbal and written
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Control - Resilient autonomy for Self-Healing Soft Robotic Platforms - Uncertainty-Aware and Predictive Human-Robot Interaction Qualifications To be qualified for the position, you must have a MSc degree in
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 2 months ago
Automata (CAFE) to considerably reduce calculation times and improve the response of numerical models. The numerical models will include laser-matter interaction, melt, and microstructure prediction models
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Position Information Position Information Working Title Manager, Biophysical Model Design (Temporary) Department Biochemistry-0831 Requisition Number S_260080 Posting Open Date 02/04/2026
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sources of quantum light for optical quantum computers. The project takes place in the Quantum Light Sources group at DTU Electro, where we design, model, fabricate and test sources of single photons
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geometries and process-induced defects demand new inspection approaches. The project combines modelling, sensor fabrication, experiment, and data analysis. You will work with a team of experts to develop
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with The School of Natural Sciences and the Discipline of Geology, seek to appoint an AIB/E3 Assistant Professor in the area of Earth System Modelling. More specifically, the successful candidate will utilize
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modeling, machine learning, or data-driven prediction methods applied to environmental datasets. Experience building and maintaining large, frequently updated archives of weather or climate observations
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areas providing a template for relevant directions: - Embodied Intelligence for Soft Robotic Systems - Foundational Models for Adaptive Soft Robots - Real-Time Adaptive and Stiffness-Aware Control