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learning or related fields; Proven experience in research work on AI models, in particular in the field of explainable AI, synthetic data generation or model testing; Proficiency in programming (preferably
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posts,PHD Thesis Starting date: 30.10.2025 Job description: DESY Foundation models are multi-dataset and multi-task machine learning methods that once pre-trained can be fine-tuned for a large variety of
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to: Development of computer models of the musculoskeletal system incorporating neural control pathways Train NMS model control policies via RL Your seconday tasks will include: Using learned NMS model control
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for environmental epidemiology (Epi, survival, sf, gstat, mgcv) and causal inference (dagitty, MatchIt), as well as contributing to reproducible, scalable data pipelines. Machine learning integration: Exploring ML
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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analysis will focus on building sophisticated Deep Learning models, e.g., Long Short-Term Memory (LSTM) networks, to accurately model DPs over time and predict mood deterioration. The project will implement
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of automatically predicting the veracity of textual claims using machine learning methods, while also producing explanations about how the model arrived at the prediction. Automatic fact checking methods often use
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We’re seeking for motivated candidates that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure, improved mechanical and corrosion properties. Research stays are planned
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under multiple environmental and socio-economic scenarios. You’ll develop sought-after skills in geospatial analysis, hydrodynamics, sediment transport, machine learning-assisted detection, and hydro