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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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will focus on designing computationally efficient, scalable, and adaptive AI models that operate under strict constraints in radio access, edge, and non-terrestrial network environments. The position is
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predictions across scales. This role requires deep knowledge of the underlying models and practical implementation skills to maximize biological impact. You will lead rigorous model evaluations, implement novel
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, operations and clinical teams to identify opportunities for revenue optimization. Oversee the design and maintenance of dashboards, KPIs and predictive models for revenue cycle management. Oversee the volume
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economics and finance. Leveraging its ‘4-in-1’ model of education and residential college system, UM provides all-round undergraduate education, nurturing talent to support social and economic development in
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, data-driven control in high dimensions has penetrated many new application areas. Examples include control of autonomous vehicles based on video data, simulation-based prediction of turbulent flows and
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Ecole Nationale des Ponts et Chaussées (ENPC) | Champs sur Marne, le de France | France | about 2 months ago
? No Offer Description Scientific overview: This PhD thesis aims at studying the impacts of climate change-induced permafrost thaw in the Arctic, by using advanced thermo-hydro-mechanical (THM) modelling
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intelligent surfaces Main supervisor: Prof. Viktar Asadchy[AALTO] Co-supervisors/mentors: Dr. Victoria Tormo [INDRA] and Dr. Barthès [3DEUS] Objectives To establish an analytical modeling approach
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their impact on gene expression. Contribute to large-scale modeling of engineered traits to predict performance and optimize design. Required Qualifications: PhD in the field of genomics, evolution, population
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. The work is part of the regional project “Optimizing Renewable Energy Integration: FPGA-Based Model Predictive Control (MPC) for Grid Stability” (Ref. SI4/PJI/2024-00238) Where to apply Website https