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, structured PhD program for all doctoral candidates working at LIV with binding guidelines developed based on the Leibniz Association's guidelines for graduate education. Our program offers multidisciplinary
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developments, as well as conceptual guidance of cross-project software developments in the field of biodiversity informatics Strategic and content-related representation of the MfN in national and international
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, enrolled in a Bachelor’s or Master’s program in economics, finance, data science, or a related field. Comfortable using Stata or Python/R (or other analytical tools). Detail-oriented, methodical and able
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master's or diploma degree in computer science or mathematics already successfully completed doctorate confident demeanor and proficient use of German and English (both equivalent to at least B2) expertise
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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program Excellent technical equipment, a wide range of experimental methods and a dynamic and interactive research environment Remuneration according to TV-L, level 13 (65 %), plus annual special payment
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an interdisciplinary framework as part of a joint research program. What will be your tasks? We are seeking a highly motivated candidate to join the newly established Collaborative Research Centre “Carbon Sequestration
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knowledge in the application and development of NGS wet lab or computational methods for the analysis of genome data for molecular biodiversity research, have strong experience in data management and analysis
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Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the
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to uncover new molecular strategies for safeguarding crops. Join a vibrant, interdisciplinary research environment where computational chemistry, biochemistry, molecular biology, and plant science converge