Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
signalling, protein interaction and metabolism Big data analysis C. Soft skills D. Annual retreat E. Thesis advisory committee F. Organisation of lecture series and meetings A Diploma supplement will be issued
-
Supervisors: Dr Raj Pandya, Prof. Nicholas Hine, Prof. Reinhard Maurer While we as humans are used to seconds and hours, electrons and atoms in materials move a whole lot faster around a million
-
. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load
-
: Rethinking everyday urban life dynamics”. The project will be under the joint supervision of Dr. Renata De Figueiredo Summa and Dr. Mayada Madbouly, with Prof. Luis Lobo-Guerrero as the promotor. This PhD
-
Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview Energy security
-
their resilience to pathogen infections. The position is available at the Plant-Insect Interactions group (Prof. Sara D. Leonhardt) as part of the TUM Department of Life Science Systems. Starting date is summer/fall
-
11.11.2024, Wissenschaftliches Personal In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the
-
43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load from YouTube. Accept cookie and
-
identity studies. Under the joint supervision of Dr Morana Lukac and Dr Suzanne Manizza Roszak, with Prof Remco Knooihuizen as the professor of record, the successful candidate will develop their own
-
Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression