Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
on experimentally realisable spin systems Cooperate and actively work with our experimental partners toward quantum simulation and quantum computing implementations using this technological platform Design and
-
-economically cost-optimal design of a process chain for the production of green hydrogen and methanol, it is necessary to carefully analyze both global and regional demand and to estimate their future
-
-body Hamiltonians on experimentally realizable spin systems Cooperate and actively work with experimental partners developing quantum simulators using this technological platform Design and implement
-
of qubits into the millions, it is crucial to move parts of the control electronics closer to the qubits. To achieve this, we design and implement cryogenic integrated circuits for qubit control and readout
-
between electrokinetic transport, surface charging, and interfacial reactivity under nanoconfinement is essential for the optimal design of next-generation ECL materials. As a PhD candidate at Theory and
-
well as in fuel cells. Your tasks in detail: Design and set-up of new testing equipment for application-driven characterization of new materials for water electrolysis Manufacturing of catalyst layers and
-
the complete chain from materials properties to process design and evaluation. More information on the project can be found here: This specific project (DC7) addresses membrane adsorbers, which have small
-
PhD Position - Modeling and simulation of memristive devices for application in neuromorphic systems
VCM cells has to be developed. Based on the models, design rules for the usage of memristive components shall be concluded. Various commercial simulation tools and self developmed environments
-
the complexity-and-performance tradeoff in different neuron models, dendritic compartments, etc.) in task-specific hardware designs, for both training and inference for identifying complex sequential patterns
-
and super resolution Collaborating on the development of domain adaptation methods for transferring learned representations to different experimental setups Designing and implementing active learning