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Field
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, reliability, and consistent behavior. Learning-based controllers can achieve high performance in complex and uncertain environments, yet ensuring predictable operation under distribution shifts, sensor noise
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modelling efforts carried out by two PhD researchers. The role includes substantial fieldwork: at least two month long campaigns and 1–3 maintenance visits over 18 months. Experience in (Southern) Africa is a
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involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and
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for the post. Examples include: Demonstrated experience in in silico protein analysis, including structural modelling, domain architecture prediction, and identification of signal peptides, processing sites, and
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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Reinforcement Learning Fine-tuning and Application of Large Language Models Time-Series Data Prediction and Modeling Intelligent Decision-Making and Optimization Algorithms Strong programming skills (proficient
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reactivity of gene-engineered T cells Qualifications Candidates most have a PhD in the area of Immunology and Cell Biology. In addition, candidates should be trained in: T cell detection technologies, using
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approach. Fundamental research focuses on induced pluripotent stem cell (iPSC)-derived neuronal models to elucidate the molecular and cellular alterations contributing to neurodegeneration in familial and
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or more of the following areas: Advanced Process Control and Optimization Digital Twin and Modeling & Simulation Predictive Maintenance and Fault Diagnosis Industrial IoT and Edge Computing Good programming
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simulations. Design, develop, and validate physics-informed AI/ML models with features from electronic structure, spectroscopy to control materials growth and emerging functionalities. Develop and train agentic