Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
Expertise in metagenomic analysis required scope (e.g. national codes and standards) Strong written and oral communication skills Proficiency in bioinformatics for amplicon and metagenomic sequencing Ability
-
-tier venues (e.g., ICSE, ASE, TOSEM, AAAI, EMSE), with at least 10+ publications, including multiple CORE A/A* papers. Demonstrated expertise in deep learning architectures, computer vision, and medical
-
their role in cellular stress responses. Experimental Design and Data Analysis Design and execute experiments using advanced techniques such as deep sequencing, mass spectrometry, iCLIP, phase separation
-
a focus on emerging threats, adversarial resilience, and trustworthy autonomous decision-making. Design and implement novel research methodologies to advance the security, reliability, and alignment
-
cortical neurons, functional loss-of-function approaches, single-nucleus RNA sequencing (snRNA-seq), xenotransplantation, and advanced in vivo imaging (e.g., 2-photon calcium imaging), the aim is to uncover
-
manage research projects, ensuring alignment with institutional research objectives Supervision of research assistants, graduated and exchange students Key Competencies and Educational Qualifications: PhD
-
require a post-doctoral fellow to engage in designing and running of multiple CRISPR genome screens, to interrogate and identify genes that are responsible for a host of different genome instability
-
network with leading universities globally. The on-campus concept provides a structured approach focused on applied research in strategically important topics aligned with Schaeffler’s strategic roadmap
-
be in close collaboration with experimental and clinical collaborators and will provide resources for large-scale data generation and full access to the latest long read sequencing technologies
-
interdisciplinary teams to align AI research with ethical standards and best practices in AI safety. Publish findings in top-tier conferences and journals, contributing to the broader AI and machine learning research