Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- ETH Zurich
- University of Basel
- Empa
- Novartis
- EPFL
- ETH Zürich
- CERN - European Organization for Nuclear Research
- Faculté de biologie et de médecine de Lausanne
- Institute for Research in Biomedicine (Bellinzona)
- Institute for Research in Biomedicine, Università della Svizzera italiana
- University of Fribourg, Section of Medicine
- 1 more »
- « less
-
Field
-
to teaching within the group. This project contains aspects of cell biology, mechanobiology, biophysics, molecular biosciences, and cell substrate engineering. Throughout the PhD, you will gain expertise in
-
. Training of IMB members in relevant areas of bioinformatics/computational biology. The candidate supports the training of PhD students and postdocs by organising individual sessions and regular teaching
-
). Preferred starting date is 6/2024. The position is for 36 months. Qualifications Our international team will welcome candidates: - with a PhD in Computational Sciences, Computational Biology or related fields
-
4 Jun 2024 Job Information Organisation/Company ETH Zürich Research Field Biological sciences » Biology Computer science » Other Neurosciences » Other Physics » Biophysics Physics » Computational
-
biology at the University of Fribourg, Switzerland to study tissue-specific immune responses (Fall 2024) The laboratory of Prof. Jens Stein at the Department of Oncology, Microbiology and Immunology (OMI
-
Role Requirements: • PhD in Oncology, Molecular and Cellular Biology or related subject area (PhD students in the last year of their thesis work, are eligible to apply). • Hands on experience with
-
at international conferences Your profile PhD in chemical engineering, electrochemistry, materials science or related disciplines Experience with slurry electrodes and electrochemical processes Experience in
-
: PhD in computational biology or related field Background in computational biology, bioinformatics or a related field Strong programming and statistical knowledge, including machine learning Excellent
-
leading life sciences institutes. With 32 groups, high-end core facilities and 500 employees, we are a dynamic and international research community that has spawned many fundamental discoveries in biology
-
methodology, complemented by microscopy and dynamic light scattering, among other methods. The aim is to develop a fundamental understanding of the leading interactions between nanoparticles and biology