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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 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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Your Job: Quantum optimization (QO) is a promising, potentially disruptive technology for solving difficult optimization problems which is at the heart of energy system design and operation. While
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-supervised learning in science Engage in national and international ML/DL communities, most importantly the Helmholtz Foundation Model Initiative Present research results at scientific meetings, conferences
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the modelling pipeline Your Profile: A university degree (Master) with subsequent PhD in Applied Mathematics, Mathematical Biology, Computational Physics/Engineering or related fields with strong relation
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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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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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contribute to the advancement of large scale "in silico" simulations applied to quantum materials science. You will play a crucial role in leading the effort to enhance code scalability on European pre
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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