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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves
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in spatial equilibrium modeling (e.g., through coursework, dissertation work, or previous projects) experience with spatial data analysis using GIS tools or spatial libraries and familiarity with
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control and optimization of electrolysis from the cell to the stack requires automated monitoring, analysis, and control of the operating parameters and processes. As part of this project, the potential
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(e.g. Python, R, …). Familiarity to work on a Linux computing cluster (HPC). Preferably experience in working with large medical image data. Vivid interest in the analysis of microscopy images or similar
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(MUCCnet: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based
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14.12.2022, Wissenschaftliches Personal The BMBF-funded position is part of the CoMPS project, which is a multidisciplinary project combining the fields of mathematics, computer science, geophysics
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gross monthly remuneration in pay group TV-E 13 is in the range €4,074 - €5,873, depending on work experience and length of service. In this project, the lower network layers and an associated integrated
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(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together
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. The purpose of the position and goal of the project is to develop and apply bioinformatic tools for the analysis of high-dimensional immunological data sets. Our laboratory (Zielinski lab) focusses on human T