Sort by
Refine Your Search
-
or biogeochemistry. Your profile We are looking for a dynamic, reliable and motivated candidate with a PhD in biology, forestry, environmental sciences or related disciplines. Strong interest in process-oriented
-
100%, Zurich, fixed-term The Grassland Sciences group is a vibrant and international working group at the Department of Environmental Systems Science at ETH Zurich. We are looking for a reliable
-
dynamic, reliable and motivated candidate with a PhD in Biology, Environmental Sciences, Quaternary Sciences or related disciplines. A background in palaeoecological research is expected and candidates
-
integrated, autonomous, and highly reliable systems for manufacturing. Job description We are seeking versatile researchers to be at the forefront of robotics. You'll bridge theoretical knowledge with
-
integrated, autonomous, and highly reliable systems for manufacturing. Job description In this role you are leading two projects: (1) the control of a secondary kinematic system for increasing stiffness and
-
independent projects and research collaborations, and supporting permanent staff in supervising BSc, MSc and PhD students working at the Geoecology group. The successful candidate will also coordinate analyses
-
at Geoecology's dating facilities and contribute to the research groups' teaching (e.g. palaeoecological and numerical practicals). We are looking for a dynamic, reliable and motivated candidate with a PhD in
-
precursors Design and execute experimental plans for systematic process parameter studies Development of appropriate synthesis setups and protocols to establish a reliable MXene synthesis platform
-
reliable quality of processed parts. Working in close collaboration with the industrial partners, you will provide the sensorization of the unique laser welding setups for real-time monitoring and detection
-
Establishing reliable databases and a real-time streaming environment for processes to build a data-centric manufacturing ecosystem Empowering intelligent manufacturing by implementing machine learning-based