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Field
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accepted. The following experience will strengthen your application: Familiarity with Federated Learning We value a collaborative attitude and an interest in working both in teams and independently. Self
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. Motivated, self-driven, and curious. Willing to learn many different techniques and analytical skills. Excellent communication skills and interpersonal skills. (highly desired but not necessary) Experience
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for candidates with completed scientific university education (Master's/Diploma) in food chemistry, chemistry or a related field sound knowledge and experience in the use of instrumental analytical methods such as
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communications Data Analysis and Management Implement and open-source proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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: excellent university degree (diploma, master's degree) in transport or related study programs with a solid basis in transport, data science, and/or data analytics; or equivalent practical experience
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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, attention to detail, and problem-solving analytical ability are important personal qualities for this position. What you will do Take courses at an advanced level within the Graduate school
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can be set up in one day. During the plant growth period the student will be trained in the appropriate analytical skills for analyses after concluding the trial (2 weeks). Scope for initiative