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Analytics Software Engineering for Distributed Systems Telematics Theoretical Computer Science Optimal Transport Work on a scientific topic aims to enable the student to understand complex scientific work
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highly accurate computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function theory. While the GW
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, both written and verbal Knowledge of German and/or a willingness to learn Computer/programming literacy, for example in R, and/or software used in image processing (Adobe Photoshop, ImageJ etc.) Ability
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programmes Much of the programme coursework requires the use of statistical programmes. Most students will use R software, although some students will use other programmes, such as Python, Stata, or SAS
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for a doctoral candidate with the following qualifications: Master's degree in meteorology, physics, mathematics, computer science or an equivalent scientific or mathematical discipline Very good
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hardware and software Adapt algorithms for effective performance on neuromorphic hardware Knowledge in at least one area as a plus: deep learning hardware development memory technology Strong problem-solving
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Schmidt University, and Hamburg University of Applied Sciences Teaching language English Languages All relevant courses are held in English. Programme duration 6 semesters Beginning Only for doctoral
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Joint degree / double degree programme No Description/content Networks, computers, sensors, and actuators are increasingly integrated into cyber-physical systems; software systems that interact with
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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new standards in computational metabolomics – facilitating biomarker discovery, advancing personalized health monitoring, and improving clinical decision-making. The work will be carried out under close