Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- ETH Zurich
- University of Basel
- Empa
- Nature Careers
- University of Zurich
- University of Geneva
- ;
- ; Ecole polytechnique federale de Lausanne - EPFL
- CERN
- EPFL
- EPFL FSB
- ETH ZURICH
- Ecole Polytechnique Federale de Lausanne
- European Magnetism Association EMA
- University of Bern
- University of California
- 6 more »
- « less
-
Field
-
existing methods, our technique aims to use laser energies that are safe for biological tissues, ensuring both efficacy and safety. To achieve these goals, two PhD projects have been designed. One of them
-
motivated Postdoctoral Researcher to join an applied research project focused on the development of AI/ML-based methods for the automation of laser processing techniques. In close collaboration with our
-
of machine learning and optimization methods in manufacturing. We aim to create intelligent systems for process parameter selection, condition-based maintenance, and human-machine interaction. Job description
-
, Environmental, and Geomatic Engineering, has an opening for a PhD student in model-based planning support for transport and urban systems under uncertainty. Planning transport and urban systems is inherently
-
of SIS (e.g., HPC systems engineers, data scientists, research software developers) and external collaborators. Profile a PhD or equivalent in Computational or Computer Science, Engineering, Physics, or a
-
analysis of data. Qualifications PhD or equivalent relevant experience in the field of PhD in the field of physics, or equivalent or a related field. Experience: This vacancy notice is addressed
-
Menu Counseling back Overview PageCounseling Individual counseling Coaching Conflict counseling Career Discussion Guidelines Postdocs and PhDs at UZH How to PhD Close Menu Funding back Overview
-
plasma. The main methods used are computer simulations for studying dust dynamics and analysing in situ measurements by spacecraft that carry a dust detector on board. We collaborate with researchers in
-
. Commercial solutions avoid entanglement-based methods due to technical challenges, yet this limits the impact such technologies can have. In this project, we aim at further developing photonic integrated
-
techniques (e.g., filter-based, morphological, and statistical methods) with machine learning approaches Collaborate with interdisciplinary teams, ensuring seamless integration of image analysis with