28 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr"-"P" PhD positions at Nature Careers
Sort by
Refine Your Search
-
data. Your profile We are looking for a motivated researcher at the PhD student level. This theory project will comprise both analytical calculations as well as numerical simulations of classical spin
-
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
-
Deadline : April 15th 2026 · Selection Process : Mai 2026 · PhD Start Date : September-October 2026 How to apply All information are provided on the website of the project : https://www.eu4greenfielddata.eu/
-
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
-
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
-
use cutting edge machine learning and data mining techniques to gain novel insights and advance our understanding of the rules defining T and B cell immunogenicity. If you are looking for the best
-
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
-
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
-
Assists in performing investigative research under the mentorship in a particular area(s) of study. Publishes and presents data in a timely manner. Works collaboratively with other investigators
-
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