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considering the potential to apply these methods to different domains. Specifically, you will: Develop, implement and refine Machine Learning (ML) techniques for self-supervised Deep Learning (DL
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PEM electrolysis. To this end, you will examine in-depth technical and economic factors. In the second part of your thesis, you will develop a detailed techno-economic electrolyzer model based
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the potential to apply these methods to different domains. Specifically, you will: Develop, implement, and refine Machine Learning (ML) techniques for self-supervised Deep Learning (DL) for scientific and large
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Your Job: However, one of the main hurdles related to AEMWE technology is to develop low-cost and robust catalysts that can withstand the harsh reaction environment without compromising
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develop suitable disaggregation methods in the second part of your thesis and apply them to the researched values. To do this, you will: Conduct a systematic literature review of current demand as
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membranes. You will develop theoretical models and employ computational methods to describe the coupling between ionic nanofluidics, electric double-layer charging, and interfacial reactivity in electrolyte
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. Following this, you will develop a load profile generator based on the insights gathered from different types of machinery, such as excavators, wheel loaders, telescopic cranes, tractors, and combine
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stability in E. coli compared to unfused enzymes. The successful candidate will Develop coarse-grained (CG) models for CAR and other enzymes of the cascade based on atomistic simulations provided by
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Your Job: Develop techniques to simulate and control the dynamics of diamond-based spin systems (e.g., NV centers) Find parameter regimes and control schemes to map few or many-body Hamiltonians
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Present research results at scientific meetings, conferences, and as scientific papers Contribute to educational events, such as university lectures, JSC courses and hackathons Your Profile: Excellent