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development opportunities and annual performance reviews. You are paid according to the collective agreement for the public sector (Tarifvertrag des öffentlichen Dienstes, TVöD Bund), which includes an annual
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development. It is one of the world's leading research institutions in its field and offers natural and social scientists from around the world an inspiring environment for excellent interdisciplinary research
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
collaboration and cooperation - intra-institute, national and international, interdisciplinary opportunities to develop – on the job and towards other positions an international environment – everyday contact
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team to work on machine learning-supported rapeseed genomics and breeding. Your tasks: You design, train and interpret deep-learning models to predict regulatory gene variants in rapeseed genomes. You
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opportunity to be an active part in the establishing of our department Comprehensive training programs and individual opportunities for personal and professional development Access to a strong research network
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the DAAD portal (Read notes on applying in the portal >> ) Prepare application documents If necessary, translate documents (unless they are already in German or English). Scan paper documents and save in PDF
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on quantum dot qubits Good software development skills Experience with sub-Kelvin cryogenic techniques Strong aptitude for mentoring students Good communication skills A strong drive to conduct ambitious
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of green hydrogen by use case. Beyond the economic feasibility, a particular focus of this position will lie on the evaluation of different development pathways when deploying green hydrogen infrastructure
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wellbeing. They will use modeling approaches to combine natural and social science data. You will focus on developing and implementing mixed modeling approaches to test pathways through which structure