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of empirical research (quantitative or experimental) methods, • knowledge of statistics, programming languages (e.g., Python), natural language processing, machine learning is advantageous but not
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of microfluidic devices. Simulation for microfluidics. (CFD) High Performance Computing and/or GPU programming for this domain. Machine learning algorithms for this domain Clean energy solutions (e.g., microfluidic
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., based on the 1D or analytical model) Hybrid simulation approach (e.g., which combine CFD and 1D simulations) High Performance Computing and/or GPU programming for this domain Machine learning algorithms
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algorithms, mechatronics, intelligent robotics and prosthetics, robot learning algorithms, foundations of machine intelligence, as well as nonlinear control and systems theory. Furthermore, we offer unified
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will need strong coding skills to design highly efficient algorithms. Solid knowledge in the areas of algorithmics, optimization problems, as well as experience with SAT/SMT solvers or machine learning
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for this position, the candidate should possess in-depth skills in programming and hands-on training and evaluating machine-learning models. Expertise in in the field of Building Information Modelling and geometric
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, Computational Linguistics, Data Science or a similar field Good theoretical knowledge and practical experience with Natural Language Processing (rule-based and/or machine learning) Software Engineering Motivation
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University Munich (www.tum.de). Accordingly, we are currently searching for PhD Students and Postdocs to join our team! PhD Students For PhD students, we are looking for persons that are willing to learn and
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skills, ability to interact with scientists at different levels good software design skills and the ability to write clean, and reusable code in machine learning, deep learning frameworks, such as
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qualification - PhD/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq analysis - interest in biological applications - passion for science