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Field
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with our staff and external users of the beamline work together with our staff to find out which resources can be shared for the project documentation of the software Your profile Required qualifications
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recognition systems and for automated, robot-assisted object reconstruction and quality inspection. What you will do You will implement and test AI methods from the field of anomaly detection as part of current
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industrial objects. Depending on the object characteristics and quality requirements, different capture systems are applied. The capture of the actual state of objects is significant in industry, particularly
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Future. Discover. Together. If you are passionate about start-ups, we are delighted to present this fantastic opportunity at HHI. Our vision? To accelerate the emergence of groundbreaking
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can find information on the use of cookies and the use of your data as well as objection options in our privacy policy. Functional External services
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resources. Scientific Objectives: Develop a system using foundation models to detect, classify, and track both stationary and moving objects from multimodal sensor data. Integrate self-learning mechanisms
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-on experience with object-oriented programming, particularly in Python, and are proficient in using libraries such as Pandas, NumPy, and Matplotlib for data processing and visualization. Data Handling Knowledge
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learning routines, such as clustering and anomaly detection, to analyze and compare large data sets of wafer parameters of interest. Data visualization and automation improvements: You design and implement
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(negotiable) Contract Duration: 36 months, full-time employment Trial Period: 6 months Project Tasks and Objectives Objectives Industry: Object detection on construction sites to verify elements of a BIM
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for the curation and archiving of various biological data, starting with information on physical collection objects, continuously extended by further data types. This development project is funded by