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Field
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for accurate and efficient analysis. Possible Research Themes We seek motivated PhD candidates to advance computational mass spectrometry in one or more of the following directions: Algorithm Development Design
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our industrial partners. You will work in the cyber analytics and CISE labs in the Algorithmics and Software Engineering Research groups at the Software Technology department under supervision of dr
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a big plus: Relevant publications (and/or M.Sc. thesis) on the above-mentioned research topics Programming Microcontrollers and Interfacing Sensors Machine Learning Algorithms and Deep Neural Networks
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with the rest of the team, you will build demonstators for the Find2Fix technology at our industrial partners. You will work in the cyber analytics and CISE labs in the Algorithmics and Software Engineering
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. This is because experimental techniques to solve structures of protein complexes favor more stable interactions with larger interfaces and because we lack efficient algorithms to compute similarity between
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, which allows for a preferred writing of elements and strong algorithmic properties, is very useful, but only few examples are known. Thomas Haettel (with Jingyin Huang, Duke Math. Journal, 2024) recently
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limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data
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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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geometry can be reconstructed mathematically (this is called inverse scattering). This requires both sophisticated mathematical models and efficiently implemented algorithms. In the case of wafer metrology