Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
-
Field
-
) for Predictive Maintenance: Introduction UM6P Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in
-
equitable energy systems. This PostDoc position is offered in collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink ). IMOS develops advanced
-
predictive maintenance in chemical plants. Key Responsibilities: Create and implement hybrid AI models that merge machine learning techniques with mechanistic frameworks (like physics-informed neural networks
-
-derived cells and single-cell perturb sequencing to establish foundational models to predict the effects of potential drug candidates on cardiovascular diseases. By combining genome engineering, functional
-
Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis
-
/2026 Back to Search Postdoctoral Research Associate, Electrical Resistivity Tomography and Environmental Geophysics Posting Number req26727 Department Biosphere 2 Department Website Link https
-
the expert models over time, addressing leakage-free training through rolling-origin protocols andthepropagation of predictive uncertainty.Task 4: Validation, benchmarking, and dissemination. Evaluate
-
Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis
-
Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | about 2 months ago
the development, maintenance and drug response in childhood cancer (Kodali et al, Nat Cell Biol 2024 ). Multiscale tissue remodeling during aging (Rendeiro lab , CeMM/LBI NetMed): This ERC-funded project builds
-
HIBEAM/NNBAR at ESS and – most relevant for this project – LDMX at SLAC (https://confluence.slac.stanford.edu/display/MME/Light+Dark+Matter+Experiment ). We exploit synergies across these projects, and our