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to gain insights and evaluate the mobile app. What you bring to the table Ideally University studies in software engineering, computer science, or a related field. Sound programming skills, especially in
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of efficiency, training performance or inference behavior What you bring to the table Enrolled Bachelor's/Master's student in full-time studies in the fields of computer science, mathematics, physics, electrical
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way. We are dedicated to current research questions on automated and cooperative driving and combine a wide range of competencies in the fields of sensor technology, communication and artificial
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thesis. What you bring to the table You are currently studying in a Master's program in Electrical Engineering, Mechanical Engineering, Materials Science, or a similar field. You have a good knowledge of
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testing and evaluation. What you bring to the table Background in Computer Science, Software Engineering, Electrical Engineering, Mechatronics or similar Enrolled student at a German university Profound
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 3 months ago
disciplines. Therefore multidisciplinary research encompassing biology, chemistry, physics and engineering is at the core of our work. We are looking for a highly motivated student with a strong interest in
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like to support us in industry-related research projects Ongoing studies, preferably in the natural sciences or in the field of electrical engineering / information technology or in a related field
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molecular biology, train scientists and students at all levels, provide essential services to both public and private sectors, develop innovative technologies and methods, and foster active technology
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a critical assessment with regard to feasibility and cost. What you will do Literature and patent research on CO₂ capture technology Critical comparison and selection of suitable absorber technologies
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electrolysis. As an MSc student, you will design and implement a suite of AI “agents” (autoencoders, statistical models, LSTMs and LLM-based rule engines) that process historical and live sensor data (voltage