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processing, quality control, integration, and analysis of single‑cell and multimodal omics datasets (e.g. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell
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: (1) automated reconstruction of a visual and geometrical 4D Digital Twin based on visual computing; (2) usage of information from digital imaging techniques for estimation and prediction of current and
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. Experience with advanced analytics, including predictive modeling, data science, or statistical analysis to support data-driven decision-making. Demonstrated experience designing and implementing ETL/ELT
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of existing studies to promote the use of risk-informed decision frameworks, prediction models, AI applied to planetary protection. Tasks include: Support the creation of probabilistic models for planetary
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research, teaching, and promoting an environment that allows all members of the department to thrive. Principal concentrations include weather prediction, air quality, air-sea interactions, climate modeling
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on the combination of Reinforcement Learning (RL) and Model Predictive Control (MPC). It will build up upon the work done at ITK on the topic. Several research focuses are considered: verification pathways in RLMPC
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learning, generalization/robustness and privacy aspects in scalable learning algorithms. Large‑scale optimization and control: Optimal control, model predictive control and other optimization‑based control
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17 Mar 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Modelling tools Geosciences » Geology Geosciences » Hydrology Researcher
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California State University, Northridge | Northridge, California | United States | about 20 hours ago
plus. Experience with advanced analytics, including predictive modeling, data science, or statistical analysis to support data-driven decision-making. Demonstrated experience designing and implementing
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identification, i.e. learning of models from measured data, and iii) real-time control, e.g. using the model predictive approach. We are working on several projects with industrial partners across the energy