Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
sequencing data is an advantage. We offer: A three-year PhD position (or four-year for Master students) in a supportive, stimulating, and interdisciplinary research environment Enrollment in PhD school
-
models. The scientist will conduct research using machine learning and classical parameterization methods on data from ocean gliders equipped with microstructure turbulence sensors, turbulence resolving
-
a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens
-
comprehensive back-office resources help manage day-to-day complexities while our investment in your venture ensures you have the means to scale quickly and capture market opportunities. Enhanced Commercial
-
a citizen science component to gain a broader data foundation and raise awareness of the issue. The results will support management measures and policy initiatives to reduce plastic pollution
-
of psychology, digital health, and artificial intelligence to advance the development and validation of voice-based tools for mental health monitoring in diabetes. The project will leverage data from the Colive
-
integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing, computational model development, data processing, and
-
A PhD position focusing on structural and functional characterization of ciliary protein complexes derived from human cells is available in the research group of Assistant Prof. Narcis-Adrian
-
data in collaboration with project partners. What we expect: The candidate has a strong interest in radiobiology and radiation physics enjoys doing research in an interdisciplinary field between biology
-
transcriptomics and single-cell RNA sequencing on patient samples • Mining and analyzing public cancer databases (TCGA, GEO, etc.) and omics data • Inferring TLS formation and maturation stages from