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Field
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programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic applications, agricultural monitoring and modeling, Agro-AI/ML, or digital twin. Instructions
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programming language (preferably Python) What we offer: A fully funded 75% doctoral position (TV-L E13) for up to 36 months • A competitive salary based on TV-L E13 for Bavaria • Enrollment as a doctoral
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studies and relevant coursework Fluency in programming and digital tools used in AI or interactive system development (e.g., Python, Max/MSP, Csound, PD, etc) is an advantage Applicants should be familiar
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in at least one major programming language, such as Python, is expected Familiarity with deep learning frameworks and modern NLP toolkits is an advantage Motivation to publish research results in
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of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
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in C++ and/or Python is expected, and experience in model analysis and parameter optimisation is beneficial. Experience in machine learning and neural networks is desirable. The successful applicant
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. - Hardware (opto-electronics) and software - Optical alignment - Model and biological sample imaging - Microscopy knwoledge - Optical imaging (theory and experiment) - Programming (Labview, Python/Matlab
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and their development Strong analytical, problem solver, and programming skills, e.g. Python, Matlab, are preferred Knowledge in Non-Terrestrial Networks and Semantic Communications is a plus Prior
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Python, and used to working with large datasets and reproducible analysis workflows. Has a demonstrated ability to initiate and drive own research ideas, preferably with experience from writing and
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. Basic proficiency in programming or scripting (e.g., Python, MATLAB, or similar) for data processing or device control. 4. Ability to set up, calibrate, and troubleshoot sensor systems (e.g., IMUs