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- Fraunhofer-Gesellschaft
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- Max Planck Institute for Intelligent Systems, Stuttgart, Stuttgart
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models. Excellent programming skills (preferably in Python) are required. Strong abstract and mathematical thinking skills. A strong interest in interdisciplinary work at the interface of software
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together to find the right job for you. What you contribute You already have some practical experience with AI and Machine Learning algorithms. Excellent programming skills (preferably with Python) are
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computer science, mathematics, or a related field with a focus on machine learning and ideally computer vision Profound knowledge of Python is strictly required and will be tested during the interview
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, Electrical, Computational Engineering, Computer Science, or a related Bachelor’s or Master’s program. Programming experience in Python, Julia, Rust, or a similar language; familiarity with Git and Linux is
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or Python You have a basic understanding of networking concepts such as subnets and firewalls and an awareness of IT security and system hardening You take user management and data security seriously
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fundamental methods such as linear regression You are comfortable programming in Python and have hands-on experience with PyTorch, including implementing and adapting neural network models You have good
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student in physics, mathematics, computer science, or a related field You have good Python programming skills and a basic understanding of quantum computing You are interested in large language models, AI
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are looking for a student assistant at the earliest possible date for the following tasks: You will model the energy flows of the greenhouse, including heat, electricity, and PV yield, using Python
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efficiently. You are proficient in software for data analysis such as MS Office, Origin or Python. You can express yourself confidently in German and/or English, both written and spoken. What we offer
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contribute The following skills are required: experience with algorithm development in Python knowledge of digital signal processing, machine learning methods, deep learning The following knowledge is