Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
to testing, programming neural interfaces, neural data analysis. Application procedure To apply, please read the full job advertisement by clicking the 'Apply' button DTU Civil and Mechanical
-
in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our
-
design to testing, programming neural interfaces, neural data analysis. We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and
-
health, though expertise in these areas is not required for applicants. The position will involve primary responsibility for data organization and statistical analysis, as well as co-authorship
-
machine learning for transport simulation. A core innovation involves Bayesian metamodeling techniques to construct fast surrogate models of the simulation space, enabling efficient scenario analysis
-
and simple quantitative research analysis of born-digital sources by leading international experts ample professional development opportunities within the area of digital history, especially in relation
-
with a background in Music Cognition, Psychology, Music Technology, or Musical Data Science, ideally with a specialisation in experimental concert research and/or collection and analysis of continuous
-
. DTU Space is involved in the full life cycle of space activities, including concept and design, construction and proto-typing, calibration and validation, implementation and operations, data analysis
-
-driven analysis and modeling. These are interdisciplinary positions that combine environmental engineering, materials science, and sustainability assessment. We are looking for motivated and forward
-
analysis with X-ray and entron diffraction. Property characterisation using a physical property measurement system (PPMS) and a SQUID magnetometer (MPMS). Ab-initio DFT calculations for property predication