Sort by
Refine Your Search
-
Your position The goal of the project is to understand the cause of multiple sclerosis, focusing on the interactions between autoreactive B cells, the lymphotropic virus EBV, and the cellular
-
in underground facilities. The project aims to evaluate sensor technologies, design and optimize multi-sensor monitoring networks, and develop advanced detection and localization algorithms adapted
-
plus. You enjoy working with complex, multimodal datasets and developing robust algorithms for continuous monitoring and predictive modelling. You are comfortable combining coding, data analysis, and
-
collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL (Prof. Olga Fink). IMOS focuses on the development of intelligent algorithms designed to improve the performance
-
flow reconstruction, enabling both real-time coarse diagnostics and high-fidelity offline velocity field estimation. Developing reinforcement learning (RL) algorithms for a multi-agent robotics system
-
offer a full suite of advanced battery materials synthesis and characterization infrastructure, including multiple gloveboxes, controlled-atmosphere furnaces, high-energy ball mills, DSC-TG-MS, Raman, FT
-
interface of multiple cutting-edge methodologies. Hands-on experimental work will be a central and substantial component of the position. Profile We are looking for a candidate with: A Master’s degree (or
-
synthesis and characterization infrastructure, including multiple gloveboxes, controlled-atmosphere furnaces, high-energy ball mills, DSC-TG-MS, Raman, FT-IR, XPS, XRD, SEM and more than 1200 battery cycling
-
2026/01/24 11:59PM Position Description The Unsteady Flow Diagnostics Laboratory (UNFoLD) led by Prof. Karen Mulleners at EPFL in Lausanne is looking for multiple PhD students to join the group in