Sort by
Refine Your Search
-
initiative. Your role will support the modelling, simulation and analysis of non-electrical infrastructures—namely gas networks, hydrogen pathways, and thermal systems—within integrated multi-vector scenarios
-
computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling
-
skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
-
Qualifications MINIMUM QUALIFICATIONS: PhD (or equivalent) in biology, bioengineering, computer science, physics, or a related field Strong scientific curiosity, motivation, and rigor Strong communication
-
for a long time and successfully discovered multiple new drug effects under this umbrella. Specifically, this position will be responsible for two projects dealing with generating signals within
-
actively contribute to the WeForming and EnerTEF projects. WeForming and EnerTEF propose developing automatized and intelligent solution for operating active distributed grids with multiple active asset6s
-
Engineering, or Electrical Engineering or Computer Science/engineering with a focus on network communications Good understanding of the 3GPP 5G radio access and core network protocols Proficiency in multiple
-
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
-
at the earliest date possible. Job Description: Innovative cultivation and extraction of marine microorganisms Investigating their chemical capacity by comparative genomics and metabolomics (computational
-
extraction of marine microorganisms Investigating their chemical capacity by comparative genomics and metabolomics (computational untargeted metabolomics using LC-MS/MS-based molecular networks) Fractionation