Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Project Description We invite applications for a fully funded PhD position in experimental proteomics. The successful candidate will contribute to a fundamental research program exploring chemical
-
2026 or as soon as possible thereafter. We expect Degree. A two-year master’s degree (120 ECTS) in Robotics, Electrical Engineering, Software Engineering, Computer Science, or an equivalent field (or a
-
Participating in the CRC 1450 graduate school and presenting research findings at internal meetings and international conferences REQUIREMENTS: A Master’s degree in Physics, Computer Science, Biomedical Imaging
-
(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
-
EU MSCA doctoral (PhD) position in Materials Engineering with focus on mechanistic study of high cor
process-performance correlations and suggest the strategies for reducing corresponding degradation rates. The best performing alloys will be tested in vitro at Hydrumedical using in house-developed flow
-
center. The newly DFG-funded Research Training Group "Biomolecular Condensates: From Physics to Biological Functions" (RTG 3120) at TUD offers an exciting interdisciplinary research environment
-
for cell tracking Participate in the CRC 1450 graduate school and presenting research findings at internal meetings and international conferences REQUIREMENTS: A Master degree in Physics, Computer
-
(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
-
atmospheric chemistry/physics. Strong qualifications within atmospheric measurement techniques (low-cost, medium-cost and advanced instruments) and experience in applying atmospheric measurements to study air
-
block within this process. You will be embedded both within an experimental and computational team, providing a unique atmosphere where there is expertise to develop the deep-learning models while having