Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
on performance and project needs. **Qualifications** • For Doctoral Candidates: Master’s degree in Computer Science, Information Systems, or Mathematics. **Applicants must demonstrate:** • An excellent academic
-
at the interface of data science and the scientific domains pursued at the three participating Helmholtz centers. Methodologically, a broad range of topics is covered, from large-scale data management to data mining
-
of Prof. Dr. Frank Cichos and Dr. Nico Scherf (Max Planck Institute for Human Cognition and Brain Sciences). The position is part of a collaborative project in the Center for Scalable Data Analytics and
-
of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
-
cells from different mouse models with accelerated aging phenotype. The work of the PhD candidate will include data mining and integration of these datasets with resulting identification of candidate
-
). The Schirmeier lab is a small multicultural research group with PhD students and postdocs of different nationalities. Thus, the group’s communication is in English. We aim to analyze the metabolic homeostasis
-
applications for a PhD Student or Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations for enzyme design Permeation and
-
complexes” During my postdoc I discovered that the TREX-complex member and RNA clampase UAP56 functions at the heart of nuclear mRNA export and orchestrates nuclear remodeling steps through its ATP-dependent
-
the egg are essential for early development, yet the molecular events that awaken these transcripts remain poorly understood. During my postdoc, I identified proteins and mRNAs localized to storage granules
-
Description Where: At the Chair for Computational and Theoretical Biology ( CCTB ) and the Center for Artificial Intelligence and Data Science ( CAIDAS ) of the University of Würzburg. Project