Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
correlative imaging. You will also contribute to method development and the establishment of a new research line in cancer cell mechanics, including optimization of protocols, documentation of workflows, and
-
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Division of Infection Medicine The research group in Structural Infection
-
programming experience basic knowledge of other mainstream programming or scripting languages experience with MLIR compiler construction framework, including dialect development and optimization passes
-
). Carry out MSC cell culture, including optimization of culture conditions, passaging, cryopreservation, and sample handling. Perform molecular and cellular characterization, process data, and compile and
-
systems. Depending on the successful candidate’s background, topics of interest include structure or dynamics inference, optimal control in and of networks, or characterization of fundamental limitations
-
to detail, scientific rigor, and a structured, systematic approach. High motivation and strong interest in developing scientific expertise and achieve research goals. A collaborative and communicative team
-
, structural optimization, and experimental methods. The department also has strong activity in X-ray and neutron methods for materials research. Project description You will carry out research and development
-
are linked to vascular co-option, abnormal angiogenesis, and a strongly immunosuppressive tumour microenvironment, enabling tumour cells to spread along vascular structures. This often results in residual
-
. The focus of the research is on experimental studies of electronic, structural, and chemical properties of materials. The Division is developing a new activity focussing on magnetic properties
-
robotic mobile manipulation: This PhD project is devoted to developing physically grounded and safety-aware learning frameworks that combine reinforcement learning with control-theoretic structure. The goal