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algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website: https://www.math.cit.tum.de/en/math/home/. The position is a full-time position (100%), initially
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for technologies Conscientiousness in implementing, testing, and documenting algorithms Curiosity about a deeper understanding of deep Learning architectures Experience in academic writing is an advantage What you
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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, and documenting algorithms High degree of proficiency in spoken and written English What you can expect Fascinating challenges in a scientific and entrepreneurial setting Attractive salary Modern and
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s
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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms (AI) to analyze large imaging and molecular
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with several research groups working in related fields, particularly in algebraic geometry and algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website
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Algorithm-HW-Codesign for wireless signal processing investigate novel hybrid imaging and coded excitation approaches for medical ultrasound reliable and resilient communications for critical applications in
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the environment, including traffic conditions, travel time, and cost. The project will define the DRL components (states, actions, rewards, policies), select and implement suitable DRL algorithms, and integrate
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning