Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Field
-
of data from laboratory-scale to full-scale. Required selection criteria You must have a professionally relevant background in applied mathematics, cybernetics, or engineering. Strong knowledge in wind
-
of data from laboratory-scale to full-scale. Required selection criteria You must have a professionally relevant background in applied mathematics, cybernetics, or engineering. Strong knowledge in wind
-
for all basic tuition in mathematics, physics and statistics at the faculty. There are currently 50 employees including doctoral and postdoctoral fellows, and 100 students at the department. Questions about
-
into account. Your PhD project will be supervised by Franziska Glassmeier. Together with two PhD students, two postdoctoral researchers, and an advisory AI team, we will tackle the challenges of the ERC Starting
-
of data. Required selection criteria You must have a professionally relevant background in computer science, applied mathematics, or engineering. Your education must correspond to a five-year Norwegian
-
on metamaterial or nanostructure design, aiming to deliver recipes for building topological optical devices. Our Research Group You will join a strong international team of students, postdoctoral and academic staff
-
the assessment of the candidate. Competence in mathematical modeling and languages for simulation or optimization of climate, energy, or transport systems (e.g., Fortran, Python, GAMS, XPress, Matlab). Competence
-
13 Apr 2024 Job Information Organisation/Company NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU Research Field Computer science Mathematics Researcher Profile Recognised Researcher (R2) First
-
such as postdoctoral fellow, Phd candidate, research assistant and specialist candidate and Regulations concerning the degrees of Philosophiae Doctor (PhD) and Philosodophiae Doctor (PhD) in artistic
-
modelling based on graph theory and population balances, mathematical tools describing changes of molecules on a coarse-grained level. The Random Graph approach is further developed to further increase