Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
understanding on the origin of nucleic acids that are shed in liquid biopsies, such as blood, using cancer models (mouse and rat) and patient samples of neuroblastoma disease, a rare childhood cancer. Nucleic
-
diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
-
pathway. Additionally, finite element theoretical modelling and density functional theory calculations will be used to further increase our understanding of the photo-reduction mechanism. Correlating
-
-specific inflammation” and aims to develop and apply advanced imaging tools to study immune cell dynamics in murine models of inflammation and cancer. More about our work: https://www.medizin.uni-muenster.de
-
-Checking, Argument Mining, Automated Planning, and Decision-Making. Training, domain adaptation, and evaluation of cutting-edge LLMs and Multi-Modal models in the cloud and on premise. Software Engineering
-
: Prof. Dr. Steven Travis Waller, Chair of Transport modeling and simulation, and co-supervised by at least one additional professor, plus an international tutor of the CRC Requirements: excellent
-
and kinetic modelling Expression, purification, and characterization of enzymes from fungal and bacterial sources Development and optimization of enzyme assays Structure–function studies of enzymes
-
the supervision of Prof. Muhammad Ali Imran and Prof Jonathan Cooper, who will act as Line Managers. The project particularly emphasizes ambient and remote sensing techniques, connectivity for healthcare, and
-
viability using multiple detection techniques (FACS, microscope, spectrophotometer). Collaboration on the analysis of created bacteria in Zebrafish models. Analyse data, contribute to scientific publications
-
are desirable, e.g., regression analyses, repeated-measures analysis, structural equation modelling, visualisation, preferably in R • Competences in quantitative research methods - ideally knowledge of several