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Are you passionate about cutting-edge fundamental research on molecular and 2D materials heterostructures? Are you looking to pursue your PhD in an excellent, interdisciplinary research environment
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the opportunity to develop her/his academic profile (PhD#degree). Requirements: Master’s degree in sociology or neighboring social sciences Desirable: - interest in one or more of the following research areas
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A PhD position is available in the Freund group at FU Berlin (https://www.bcp.fu-berlin.de/en/chemie/biochemie/research-groups/freund-group/index.html). The position is limited until June 30, 2028
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), and computational modeling (deep neural networks). We apply multivariate analysis methods (machine learning, representational similarity analysis) and encoding models. Job description: This is an open
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to study complex biophysical processes on long timescales. We use data-driven methods for systematic coarse-graining of macromolecular systems, to bridge molecular and cellular scales. We work on a
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the framework of the project using statistical methods. - Contribution to academic publications based on project’s results. - Administrative support of the project, its events and activities. The employment
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Obligation Regulation (LVVO) - participation in academic self-administration Requirements: - Completed academic university degree (Master’s or Diploma) in Chemistry or Biochemistry - completed PhD in Chemistry
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The Professorship of Empirical Methods in Social Research works on how to use cutting-edge research methods in order to better understand some of the main issues in society and politics today
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spectrometry and programming skills. The position is very suitable for a Master's thesis. Furthermore, the working group plans to establish a PhD position in this field in the course of 2026. Although a
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theoretical and practical experience with machine learning methods, especially for training of machine learning potentials - development and utilization of ab initio electronic-structure methodology - previous