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28.01.2026, Academic staff We are looking for a team lead with knowledge in electrochemistry that will lead our activities in RDE/RRDE and flow cell operation coupled to operando analytics, e.g. ICP
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well as an active engagement in the 3RTG activities. Requirements: successfully completed university degree (Master's, Diploma or equivalent) and relevant PhD in Computer Science, Computer Engineering, or related
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Analytics and Operations Research Details: https://www.science.hr/jobs/216064/research-and-teaching-assistant-phd-… Where to apply Website https://www.science.hr/jobs/216064/research-and-teaching-assistant
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: (1) contributing to the development of new analytical tools for the empirical assessment and comparison of welfare state institutions, (2) leading and coordinating the collection of legal information
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conferences Preparation of publications Maintenance of laboratory standards and equipment Co-supervision and teamwork with students German language skills are an advantage but not required Qualifications PhD in
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 17 days ago
19 Jan 2026 Job Information Organisation/Company Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association Research Field Other Researcher Profile Recognised Researcher (R2) Established
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scientific journals Requirements: completed scientific university degree and, if applicable, PhD: either in computer science, data science, bioinformatics, or a related field with a focus on machine learning
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- Familiarity with data visualisation software (e.g. Tableau, R-Shiny) would be an asset - Strong analytical skills - Organisational skills as well as the ability to work both independently and as part of a team
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local partners PhD degree in analytical chemistry, biological or food chemistry, biochemistry, biotechnology, pharmacy or a comparable natural science discipline Experience in a core facility, service
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-, ground-, and simulation-based data on the landscape water balance with data analytics to understand how variations in connectivity influence hydrograph characteristics, e.g. flood peaks and drought