Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
-
into the mechanisms that lead to the activation of ferromagnetic order through rigorous experimental studies as well as simulations. Proof-of-principle studies to observe the response of generated spin-textures
-
and the effects of disordered correlated microstructures on diffusion; iii) development of energy-based models and numerical simulations of hyperuniform assemblies; iv) development and application
-
mineral and metal-bearing raw materials more efficiently and to recycle them in an environmentally friendly way. The Department of Modelling and Evaluation is looking for a PhD Student (f/m/d) to work in
-
living allowance, a mobility allowance and a family allowance (if eligible)) starting November 1, 2025. Research areas: DC7: Programming models and high-level compilation for near-sensor dataflow execution
-
consisting of PAT and mechanistic / data driven modelling allowing process control. Steps to be taken will be: Developing a process applicable PAT method (single / multisensoric) for AAV / LNP / VLP detection
-
on mesoscale fluid dynamic simulations, microclimatic and turbulence modelling procedures in urban environments shall be performed. Subsequently weather-and turbulence-related limit values shall be formulated
-
Description The Chair of Transport Modelling and Simulation at TUD Dresden University of Technology is investigating models, algorithms and simulations to achieve an enhanced scientific
-
well as Mobility Modeling and Simulation. Research topics range from conceptual issues of strategic planning to small-scale analyses of specific street spaces. The chair’s methodological focus is on the empirical
-
for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks