Sort by
Refine Your Search
-
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
-
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
-
(Methods for Active Informed Machine Learning). This project is a close collaboration with the Hasso Plattner Institute. We are developing and improving machine learning methods by integrating domain
-
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
-
), 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
-
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
-
methods for data analysis and integration. Our research questions often originate from the life sciences or the (public) health sector. We integrate different levels of data and develop combined
-
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
-
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
-
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