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Field
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advanced statistical/chemometrics and machine learning tools, iv) to couple metabolome data with other omics datasets (e.g., genomics, lipidomics, metallomics, and others). Main target areas are drug
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optical communication networks and systems, as well as machine learning, computer vision, and compressing digital videos. Become a part of our team and join our scientific team in the multimedia
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-driven energy systems research – scalable, transparent, and interoperable. Your tasks in detail: Development of a structured description format for the unambiguous and machine-readable characterization
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? You are studying Mechanical Engineering in the field of Aviation or Shipping. Do you have knowledge of design and machine elements? Are you proficient in CAD and maybe even have first experiences in FEA
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of study Good Java and/or Python programming skills Machine learning knowledge and experience Experience with Static Analysis is recommended Good language skills in German and/or English What you can expect A
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machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems Further scientific development
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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the field of biotechnology, bio-/chemical engineering, (bio) process engineering, bioinformatics, biophysics or biomathematics. Ideally you have Programming skills and knowledge on machine learning and
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! What
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biological samples' 3D structure and molecular identity. At iBIO, we bring together cutting-edge science from biology, chemistry, engineering, and computer applications. Our overarching aim is to obtain a