24 molecular-modeling-or-molecular-dynamic-simulation Postdoctoral positions at Aalborg University
Sort by
Refine Your Search
-
Postdoctoral Position in Probabilistic Machine Learning for Spatio-Temporal Data Modelling A postdoctoral position is available at the Department of Computer Science, Aalborg University Copenhagen
-
electrolysis and grid connection. Knowledge in system modelling and dynamic thermal modelling is important. The position may also include experimental work on hydrogen and e-fuels. The position is offered in
-
, we do not know the neuronal pathways. Thus, we wish to study the molecular mechanistic impact of calmodulin mutations in neurons. As our model system, we will establish cultured neurons derived from
-
power converter topologies (e.g., Dual-active-bridge, LLC, and resonant converters). 2)Power converter design and optimization. 3)Multi-domain modeling simulation (e.g., electro-thermal). 4)Wide-band-gap
-
expertise within molecular methods development, bioinformatics and machine learning. Furthermore, the position will be anchored in the Center for Microbial Communities that has approx. 50 scientists working
-
Metagenomics group with 15 researchers at various career levels with expertise within molecular methods development, bioinformatics and machine learning. Furthermore, the position will be anchored in the Center
-
with 15 researchers at various career levels with expertise within molecular methods development, bioinformatics and machine learning. Furthermore, the position will be anchored in the Center
-
. The goal is to quantify both the extent of material degradation and its precise spatial distribution within the battery structure. By modeling the battery as a dynamic 3D acoustic landscape, we expect to be
-
simulation of circuits in QSpice and LTSpice and programming of design tools using C and Phyton. The hardware test platforms are controlled by microcontrollers and it is needed to program the microcontrollers
-
. The Postdoc will conduct research on methods to enhance the performance, safety, and lifetime of lithium-ion batteries by integrating physics-based modeling with data-driven approaches. The work will include