114 data "https:" "https:" "https:" "https:" "Dr" "Goethe University" PhD positions at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains
-
various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
-
(SNSPD). Additional responsibilities include developing efficient coupling of free-space optics to optical fibers, conducting extended data-taking runs with TES and SNSPD systems, and performing data
-
applications of macrosopic quantum coherence in levitated solidstate platforms. Our Team is part of the Quantum Optics, Quantum Nanophysics and Quantum Information group of the Faculty of Physics. We are member
-
academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
-
, CRISPR-Cas systems, microRNAs, non-coding RNA, RNA biology of infections, and RNA chemistry. Applicants can choose a mentor who best matches their interests and background (more information under “Panel
-
analysis to extract information on atomic dynamics from image series. Investigate molecular adsorption, surface reconstruction and site-dependent reactivity at the single-atom level Understanding of atomic
-
research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves
-
materials synthesis, advanced operando characterization, and lab scale testing. We use robotic, high-throughput methods, and data science to accelerate novel sustainable materials discovery. PhD Position
-
(graduated or close to graduation) in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, Applied Mathematics, or related fields. Scientific curiosity and creative thinking