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Field
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experimental molecular biology and data analysis. Doctoral candidates can specialize in genomic and molecular biology techniques, as well as in algorithms, statistics, and artificial intelligence for molecular
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Familiarity with statistics and programming experience in Python are advantageous Strong intention to be a part of international team with interdisciplinary questions We offer: An interesting and vibrant field
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module I: Basics in quantitative and qualitative methods Compulsory module II: Statistics and econometrics or Advanced methods in qualitative research Compulsory module III: The sociological and economic
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simulation software, e.g., SUMO, MATSim, etc. Good command of a statistical or procedural programming language such as R, python, julia, matlab, etc. Interest in transport policy We offer We offer a full-time
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Helmholtz Centre for Environmental Research - UFZ • | Leipzig, Sachsen | Germany | about 2 hours ago
. At the UFZ, doctoral researchers are supported by a range of additional services, e.g. Statistics Support, Bioinformatics Service, Family Support Office, International Office, etc. Course organisation HIGRADE
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degree (PhD equivalent). Outstanding (top 10%) students holding a Bachelor's or Master's degree in economics or related fields (e.g., mathematics, statistics, business administration, accounting, and
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) Conception and implementation of device and test specifications Technical and statistical evaluation of measurement results as well as circuit and device documentation Taking on initial project responsibility
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of Reference for Languages (CEFR) Technical equipment and programmes Much of the programme coursework requires the use of statistical programmes. Most students will use R software, although some students will
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(compulsory) Lecture series Expert courses Summer schools Soft skills courses Training in scientific programming and statistic software Project management, computer literacy Presentation, communication Writing
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, (food) marketing, or related social sciences disciplines, strong analytical skills, experience with relevant statistical methods, proven interest in topics related to sustainable food systems, and strong