319 computer-science-programming-languages-"O"-"O" Postdoctoral positions at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
degree in molecular biology, cardiovascular medicine, biology or computer science Strong background in bioinformatics, mass spectrometry, epigenetic and NGS approaches preferred At least one first-author
-
' datasets - genomics transcriptomics, and proteomics Proficiency in R, Python, and other programming languages Expertise in Linux, Git, Docker, and other high-performance computing environments Excellent
-
laboratory experimental experience. · You have programming experience, knowledge of Python and Git is a plus. · You have a proven ability to write high-quality scientific papers. Language
-
applications in fundamental research, biotechnology and synthetic biology. Our multidisciplinary research combines high-throughput genome editing, state-of-the-art genomics methods, and computational biology
-
scientific organisation. With around 1,200 employees as well as ca. 500 guest researchers, we contribute to the Helmholtz Research Field Earth and Environment, aligning cutting-edge research with societal
-
Computer Science, Artificial Intelligence, Cybersecurity, or related fields Expertise in AI and ML applications for cybersecurity and threat analysis Knowledge of supply chain security challenges and
-
supporting diversity at our centre, we actively promote women in science and in leadership positions. We among others do this through our gender equality plan and the cascade model measures which we actively
-
and clinical translation. Supported by the Carl Zeiss Foundation , an ERC Starting Grant , and the DFG Emmy Noether Program, our lab provides a highly collaborative and interdisciplinary environment
-
· An environment encouraging curiosity, innovation and entrepreneurship in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international
-
computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and