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, statistical analysis, and machine learning-enabled decision-making • Prototype, integrate, and optimise suitable open-source hardware and software solutions for automated experimentation, including laboratory
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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present. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python skills, preferably some
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hash functions for image recognition OSINT and crawling, social media and the dark web / cryptocurrencies Machine learning for data analysis AI security: Attacks on deep learning (classifiers, LLMs) and
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Knowledge in the field of Machine Learning, including training, inference, and optimisation of transformer architectures Knowledge in the field of ML security is desirable. Good Python skills, especially with
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with python programming, image processing, agent-based systems Ideally, good communication skills in both German and English You are enthusiastic about learning new practical skills, approach unfamiliar
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, imaging). • Solid foundations in signal processing and statistics. • Experience with machine learning for regression (e.g., tree-based methods, neural networks) • Hands-on experimental skills: ability and
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and evaluation of innovative data-driven and Machine Learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop novel optimization
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data processing, image/signal analysis, and machine learning. ✅ Familiarity with instrument control, calibration, and automation workflows. ✅ Excellent written and oral communication skills in English
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, engineers, computer scientists, and medical researchers — develops next-generation computational models to interpret complex biomedical data across multiple scales. Our innovations in tissue clearing, 3D