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for tactile sensors • Application of machine learning methods for object recognition and optimization of the gripping process What you bring to the table • Studies at a university or college in
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update efforts, you will investigate methods that facilitate domain generalization of machine learning algorithms in computer vision. What you bring to the table Good knowledge in machine learning and
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relevant packages for machine learning. Additional experience with libraries in reinforcement learning or, graph neural networks would be a plus. You are not afraid of learning new technologies and
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engineering or comparable ⦁ Knowledge of statistical methods and machine learning ⦁ Knowledge of the programming languages Python and/or R ⦁ Ideally initial experience with common ML libraries and
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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Would you like to improve your programming skills and apply your knowledge in the field of machine learning? For our ongoing research projects, we are seeking exceptional candidates to write
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, we offer you personal supervision at eye level and teach you how to manage and carry out experiments and projects independently in a short space of time. We guarantee creative and innovative projects
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Good knowledge of Java, Python, HTML, ROS, or comparable Basic knowledge in the field of machine learning Good communication and willingness to work in an interdisciplinary manner What you can expect
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 32 000