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digitisation, archiving and utilization programme. Due to an expected broad public and scientific interest in the HEFA, very good communication skills are essential for networking with national and international
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, weighing and chemical extraction Data entry and evaluation Literature research Your qualifications Enrolment in a Bachelor’s or Master’s degree programme in environmental or natural sciences or equivalent
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The Leibniz Institute for Solid State and Materials Research Dresden e. V. (IFW Dresden) conducts modern materials research on a scientific basis for the development of new and sustainable materials and technologies. The institute employs an average of 500 people from over 40 nations and, in...
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parking) 30 days of vacation Participation in the benefits program for employees („Corporate Benefits“) The advertised position is available for 3 years. We look forward to welcoming a team player with high
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Bachelor (advanced) or Master program with a focus on political science, economics, data science, statistics, or a related discipline; Excellent knowledge of the English language (the working language of
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-responsive proteins to develop genetic switches and circuits in therapeutically relevant bacteria. Your tasks: Use computational tools to design protein structures with desired properties Produce
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The INM – Leibniz Institute for New Materials in Saarbrücken, Germany, is an internationally leading center for materials research, a scientific partner to national and international research institutions, and a research and development provider for numerous companies throughout the world. The...
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encourages independence and self-reliance aervice groups and support for stakeholder management and living lab coordination, as well as for data management and computation access to a network of national and
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coordination with Prof. Dr. Harald Sack. Qualifications and Skills: A very good PhD degree in computer science or a comparable discipline. Very good software engineering skills. Excellent written and spoken
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datasets. Developing and implementing data processing workflows to create high-quality visualizations and maps. Utilizing PIK's high-performance computing cluster for spatial and temporal data analyses