60 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" uni jobs at Forschungszentrum Jülich
Sort by
Refine Your Search
-
remuneration for your thesis In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits We welcome applications from people with diverse backgrounds
-
, you will be an active member of the SDL “Fluids & Solids Engineering” and will collaborate strongly with the SDL “Applied Machine Learning”. You will have the following tasks: You will work together
-
projects SCIENTIFIC ENVIRONMENT: You can expect excellent scientific equipment, modern technologies, and qualified support from experienced colleagues. On top, you will receive individual training to learn
-
experience in scientific computing and software development; familiarity with C++ and Linux environments is an advantage Strong background in deep learning for image analysis / computer vision, ideally
-
the collected data in accordance with FAIR standards for collaborative use within the Decode project and for machine learning applications Presentation of results in team meetings and preparation of a
-
mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time-lapse data Proven programming expertise in
-
environment, we offer you much more: https://go.fzj.de/benefits We welcome applications from people of diverse backgrounds, in terms of age, gender, disability, sexual orientation/identity as
-
! This job offer is closely linked to a related opening at IET-3 at Forschungszentrum Jülich within the same project consortium: https://www.fz-juelich.de/en/careers/jobs/2025-362 Please feel free to apply
-
of the work Your Profile: Master student in biology, biotechnology or related field Interest in cloning, microbial cultivations and genetic engineering Willingness to learn new methods and engage with subject
-
on these considerations, solutions will be developed and implemented to create an advanced testing platform for the comprehensive evaluation of the long-term stability of invasive brain-computer interfaces. Your task will