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genomic data using deep learning methods in order to identify degrading enzymes from different data resources Using Hidden Markov Models and similar tools as well as machine learning for the identification
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Your Job: Developing and implementing QC algorithms (QAA, QAOA, QSVM), quantum AI algorithms, use case adapted algorithms to test and benchmark latest technology focusing on gate-based QC Advancing
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. The current project deals with the use of machine learning / artificial intelligence and big data science in the field of synchrotron research. Development and application of machine learning / artificial
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Your Profile: Required qualifications and skills: Scientific university degree (Master’s) followed by a PhD in Physics, Chemistry, Material Science or related disciplines Profound knowledge
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projects Your Profile: Master Degree and PhD in plant sciences, plant biology, plant physiology, agriculture or other related disciplines Solid background in whole plant eco-physiology, plant growth and / or
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Offer: We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you in your work with: Access to and discretionary
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Your Job: Analysis and integration of diverse biological data from the field of plant sciences (next generation sequencing, large scale genomic, transcriptomic, proteomic, metabolomic and phenotypic
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the form of publications in relevant journals Your Profile: Very well completed scientific university (Master and PhD) studies in informatics or computational science Strong mathematical background Extended
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proposals Support in establishing the institute Your Profile: Master`s degree with PhD in physics, chemistry, materials science, chemical engineering, or related disciplines Fundamental knowledge in
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`s degree with PhD in physics, chemistry, material science, chemical engineering, or related disciplines Extensive knowledge of X-ray diffraction, X-ray optics and X-ray instrumentation Experience in