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39-21272 Date of filling: As soon as possible Application deadline: 31.12.9999 The Neural Data Science Lab (Prof. Ecker) and the Machine Learning Lab (Prof. Sinz) of the Institute of Computer Science
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objective is to facilitate atomistic materials science with machine learning to gain insight into fundamental processes on the atomic scale and accelerate materials development. YOUR ROLE AND GOALS You will
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and food economics (incl. consumer behavior) Sustainable food systems Machine learning, AI and digital agribusiness management International agricultural development The job responsibilities include
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candidate to join our team to contribute to a project which will focus on the development of machine learning (ML) architectures for predicting and designing enzymatic reactions. To create the ML framework
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The Model-driven Machine Learning group, lead by David Greenberg at Helmholtz-Zentrum Hereon, seeks two curious and driven postdocs to start as soon as possible. They will work at the absolute forefront of AI
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at the chair of computer architecture for a duration of 2 years with the possibility of extension for up to 6 years. You will be working with PhD students in the group working on various aspects and levels of in
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. UKF jobticket UKF Your challenges: develop and optimize high-throughput analysis pipelines integrate complex RNAseq, Whole Exome Sequencing and TCR repertoire high-throughput data apply machine learning
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) #write, publish and present research in scientific journals and conferences Your profile #PhD in mathematics, physics, machine learning, computer science or the geosciences #can carry out research
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10 people), working on the open source software NOMAD . As a postdoctoral researcher, you will also be involved in research on method development for machine learning algorithms and advise PhD
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Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ | Potsdam, Brandenburg | Germany | about 1 month ago
: Geophysics), we are looking for a: Reference Number 9366 You will be working on the MIPT project: Ionospheric and plasmaspheric dynamics from observations, machine learning and physics-based modeling Our