{"id":487,"date":"2015-03-27T09:16:14","date_gmt":"2015-03-27T09:16:14","guid":{"rendered":"http:\/\/www.www.lasar.polimi.it\/?page_id=487"},"modified":"2024-01-18T10:13:30","modified_gmt":"2024-01-18T10:13:30","slug":"work-with-us","status":"publish","type":"page","link":"https:\/\/www.lasar.polimi.it\/?page_id=487","title":{"rendered":"Study and do research with us"},"content":{"rendered":"\n

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PhD POSITIONS<\/strong><\/h1>\n\n\n\n
\n\n\n\n

MASTER THESES<\/strong><\/h1>\n\n\n\n

Theses with international collaborations:<\/em><\/strong><\/h2>\n\n\n\n

Theses on risk and resilience assessment of complex systems and critical infrastructures:<\/em><\/h3>\n\n\n\n

Guided probabilistic risk assessment of complex systems using reinforcement learning optimization (with UCLA, USA)<\/a><\/p>\n\n\n\n

Resilience assessment and management of power grids in response to extreme weather conditions (heat wave, storm, flood, wildfire, etc.) (with UCLA, USA)<\/a><\/p>\n\n\n\n

Optimal sensor placement for efficient state and performance monitoring of interdependent complex systems, Case study: power grids (with UCLA, USA)<\/a><\/p>\n\n\n\n

Exploration of optimization methods for guided probabilistic risk assessment of complex systems (with UCLA, USA)<\/a><\/p>\n\n\n\n

Development of a neural network for Critical Heat Flux predictions (with CEA, France)<\/a><\/p>\n\n\n\n

Physics Informed Deep Learning to Improve Predictive Capabilities, Interpretability and Reduce Uncertainty of Modeling and Simulation of Nuclear Microreactors (with MIT, USA)<\/a><\/p>\n\n\n\n

Real-Time Condition-Informed Safety Assessment of a Microreactor (with MIT, USA)<\/a><\/p>\n\n\n\n

Inverse Uncertainty Quantification with Deep Learning Surrogate Models of<\/a>
Accident Scenarios in Nuclear Microreactors (with MIT, USA)<\/a><\/p>\n\n\n\n

Development of a Digital Twin of a Nuclear Microreactor: on the Multi-fidelity<\/a>
Uncertainty Quantification (with MIT, USA)<\/a><\/p>\n\n\n\n

Modeling the Competing Diffusion of Information vs Disinformation and Resulting Infrastructure Impacts (with University of Oklahoma, USA)<\/a><\/p>\n\n\n\n

Identifying Relationships Between Information and Physical Layers with Signal Analysis (with University of Oklahoma, USA) <\/a><\/p>\n\n\n\n

Advanced methods of dynamic risk assessment for energy systems (with Leibniz University of Hannover, Germany)<\/a><\/p>\n\n\n\n

Extended Survival Signature Approach for Multi-state Systems (with Leibniz University of Hannover, Germany)<\/a><\/p>\n\n\n\n

Semi-Supervised Class-Imbalance Learning for Identifying Rare Events (with University of Windsor, Canada)<\/a><\/p>\n\n\n\n

Safety analysis of nuclear power plants: quantification of the uncertainty in nuclear thermal-hydraulic codes based on heterogeneous experimental data<\/a><\/p>\n\n\n\n

Data adequacy assessment in thermal-hydraulic experimental tests of Intermediate Break Loss of Coolant Accident (IBLOCA)<\/a><\/p>\n\n\n\n

Theses on reliability assessment:<\/em><\/h3>\n\n\n\n

Development and implementation of uncertainty propagation methods for the estimation of early-life failure probability of semiconductor devices (with INFINEON)<\/a><\/p>\n\n\n\n

Advanced Monte Carlo simulation for efficient dynamic reliability assessment of polymer electrolyte membrane fuel cell systems (with Leibniz University of Hannover, Germany)<\/a><\/p>\n\n\n\n

Development and implementation of Tools for the Availability and Reliability Assessment of the CERN Complex Technical Infrastructure Systems (with CERN, Switzerland)<\/a><\/p>\n\n\n\n

Theses on Prognostics and Health Management for Predictive Maintenance:<\/em><\/h3>\n\n\n\n

Artificial Intelligence-Based Prescriptive Maintenance by Federated Learning (with CNR and CERN)<\/a><\/p>\n\n\n\n

Development and implementation of prognostics and health management methods based on image processing (with INFINEON)<\/a><\/p>\n\n\n\n

Uncertainty-driven AI methods for Prognostics and Health Management (with ETH Zurich, Switzerland)<\/a><\/p>\n\n\n\n

Development of State-of-Health Indicators for Researchable Batteries Using Deep-Transfer Learning Methods (with Ecole Polytechnique, France)<\/a><\/p>\n\n\n\n

Deep Transfer Learning Methods for Prognostics and Health Management (PHM) of Batteries (with Tsinghua University, China)<\/a><\/p>\n\n\n\n

Theses with industrial partners:<\/em><\/strong><\/h2>\n\n\n\n

Theses on risk and resilience assessment of complex systems and critical infrastructures:<\/em><\/h3>\n\n\n\n

Electrical network resilience (with ARAMIS Srl, Italy)<\/a><\/p>\n\n\n\n

Offre de stage au sujet de la diversification des syst\u00e8mes \u00e9lectriques du nouveau nucl\u00e9aire (with EDF, France)<\/a><\/p>\n\n\n\n

Theses on reliability assessment:<\/em><\/h3>\n\n\n\n

Application du \u00ab model-based system engineering \u00bb (MBSE) aux \u00e9tudes de fiabilit\u00e9-disponibilit\u00e9maintenabilit\u00e9 (with ALSTOM, France)<\/a><\/p>\n\n\n\n

Theses on Prognostics and Health Management for Predictive Maintenance:<\/em><\/h3>\n\n\n\n

Analisi multi-fonte dei dati di risorsa vento per un progetto di impianto eolico (with EDISON, Italy)<\/a><\/p>\n\n\n\n

Intelligenza artificiale, tecnologie robotiche e big-data per la manutenzione predittiva degli impianti eolici (with EDISON, Italy)<\/a><\/p>\n\n\n\n

Large-scale multi-modal online health monitoring and fault-tolerant control technology for sensors of the Distribution Control System (DCS) of Nuclear Power Plants (NPPs) (with China Nuclear Power Engineering Co., Ltd)<\/a><\/p>\n\n\n\n

Train Diagramming (with ARAMIS Srl, Italy)<\/a><\/p>\n\n\n\n

PHM impact on Life Cycle Cost Analysis (with ARAMIS Srl, Italy)<\/a><\/p>\n\n\n\n

Other:<\/em><\/h3>\n\n\n\n

Development of an Artificial Intelligence-based Virtual Meter Tool for Carbon Capture and Storage Applications (with ENI, Italy)<\/a><\/p>\n\n\n\n

Development of machine learning techniques for data-driven DWIM systems (with ARAMIS Srl, Italy)<\/a><\/p>\n\n\n\n

Physics-informed neural network for modeling high burnup structure formation in nuclear fuel (with NRG, Italy)<\/a>.<\/p>\n\n\n\n

Theses internal at LASAR:<\/em><\/h1>\n\n\n\n

Theses on risk and resilience assessment of complex systems and critical infrastructures:<\/em><\/h2>\n\n\n\n

Ecology network analysis methods for balancing efficiency and resilience of critical systems and infrastructures<\/a><\/p>\n\n\n\n

Resilience of energy production plants exposed to Natural-Technological (Natech) scenarios of increasing frequency and severity in the climate change context<\/a><\/p>\n\n\n\n

Uncertainty quantification methods in the risk analysis of energy systems exposed to NaTech hazards and accident scenarios<\/a><\/p>\n\n\n\n

Uncertainty Quantification in Computational Fluid Dynamics (CFD) for Risk Assessment<\/a><\/p>\n\n\n\n

Methods for the evaluation and optimization of the resilience systems, plants and infrastructures<\/a><\/p>\n\n\n\n

Advanced methods for the risk assessment of industrial facilities and plants in the oil&gas and energy sectors<\/a><\/p>\n\n\n\n

Climate change impact on the risk assessment of energy production plants<\/a><\/p>\n\n\n\n

Theses on Prognostics and Health Management for Predictive Maintenance:<\/em><\/h2>\n\n\n\n

Deep Learning Methods for Extracting Information from Text Documents in Prognostics and Health Management Applications<\/a><\/p>\n\n\n\n

Development and implementation of diagnostic techniques for the classification of abnormal conditions in industrial plants using transparent rules<\/a><\/p>\n

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  PhD POSITIONS MASTER THESES Theses with international collaborations: Theses on risk and resilience assessment of complex systems and critical infrastructures: Guided probabilistic risk assessment of complex systems using reinforcement learning optimization (with UCLA, USA) Resilience assessment and management of power grids in response to extreme weather conditions (heat wave, […]<\/p>\n

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