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Field
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predictive control (MPC), data-driven approaches, and physics-informed models. Perform dynamic simulation and techno-economic and environmental assessment under real operating conditions and uncertainty
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the Karoo Basin (South Africa) and other exhumed systems and subsurface systems from the North Sea/NCS, to develop models of deep-marine lobe successions as fluid flow pathways and storage containers for CO2
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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. The place of work will be at campus Porsgrunn. About the doctoral project The person appointed will be affiliated with the research project pavement materials and fatigue damage modelling, which is headed by
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between ocean circulation and biogeochemical cycling in modulating marine ecosystem responses to global warming. The work will provide an opportunity to develop model simulations, contribute to both
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. Develop AI, machine learning, optimisation, and decision-support algorithms. Build digital twin environments, physics-based modelling, concept evaluation frameworks, and technical risk assessments. Develop
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functional materials and membranes. Perform separation experiments and evaluate membrane performance. Carry out data analysis, AI-assisted analysis, modelling, and/or simulation studies. Draft reports and
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); 2. A detailed Curriculum Vitae (in English); 3. A copy of the Master Certificate; 4. The email contact of up to 3 referees. Non-compliance with this documents/information determines
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to computational models. The group has a leading role in European within the fields of unconventional computing, our Comet initiative , and Computer Architecture, our CAL initiative . The position will be part of
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, simulation, controllable generation, reasoning, planning, and decision-making. Build benchmarks, datasets, and evaluation protocols for world models, LLMs, and multimodal AI systems. Conduct experiments