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for optimizing metals microstructures in-situ during the AM process as well as ex-situ during post-AM treatments and enable predictions of the microstructural evolution, and thus changes in properties, while AM
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deep learning models, testing and optimizing the models documenting all performed tasks in detail, visualizing the model results, and writing technical reports investigating related software and
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production environments, enabling predictive maintenance and data-driven optimization through centralized data platform architectures. Your research will focus on addressing current bottlenecks in data and
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The AarhusNLP Group at the Center for Humanities Computing, Aarhus University, invites applications for multiple three-year Postdoctoral Researcher positions. Starting date: June 1 2025 (or as soon
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objective is to surpass the current traditional thermodynamic and optimization approaches, which are constrained in design discovery capabilities and long-term TES performance evaluation. Through your
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for industrial production focusing on Tenebrio and black soldier fly. The tasks will include: Establishing nutrient requirements for optimal production and resource utilization in insects produced at an industrial
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. Responsibilities and qualifications Qualifications: PhD degree in Engineering, Physics, Computer Science, or Applied Mathematics. Proficiency in scientific programming with Python. Excellent oral and written
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, bioactive compounds, and other key nutrients. Develop and apply machine learning and modeling techniques to analyse, predict, and optimize the effects of processing on food composition, food Ingredient
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Associate Professor or DTU Tenure Track Assistant Professor (junior group leader) in High-through...
of microbial strains. A key aim will be to uncover the molecular-genetic foundations of performance, enabling more accurate selection and optimization of candidate strains. You will work closely with DTU teams