Sort by
Refine Your Search
-
Country
-
Employer
- UNIVERSITY OF VIENNA
- Stanford University
- University of Washington
- Aarhus University
- Baylor University
- Empa
- Pennsylvania State University
- University of Vienna
- Vrije Universiteit Brussel
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- Yale University
- Computer Vision Center
- EPFL
- European University Institute
- Heidelberg University
- Indiana University
- Institute for bioengineering of Catalonia, IBEC
- Max Planck Institute of Animal Behavior, Radolfzell / Konstanz
- New York University
- Norwegian University of Life Sciences (NMBU)
- Radboud University Medical Center (Radboudumc)
- Saarland University
- SciLifeLab
- Umeå University
- University of Amsterdam (UvA)
- University of California
- University of California Irvine
- University of Massachusetts Chan Medical School
- University of North Carolina at Charlotte
- University of Virginia
- Washington University in St. Louis
- universitypositions
- 22 more »
- « less
-
Field
-
for highly motivated postdoctoral candidates with a PhD in bioengineering deep knowledge in computational biology and machine learning. Candidates with a molecular biology or engineering degrees with
-
. Experience with deep learning and programming, preferably in Python, are required and should be evident from your academic track record, including the (online) courses you've followed, your publications
-
boson decays, searches for supersymmetry and other new phenomena, and measurements of rare standard model processes. We vigorously pursue the use of machine learning techniques for data analysis
-
/Qualifications Strong research track record in AI and scientific applications. Excellent knowledge of Machine Learning and Deep Learning. Strong Python programming skills. Experience with PyTorch, TensorFlow
-
future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
-
future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
-
(postdoc) Reference no.: 5955 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate about
-
network inference and modeling, machine learning and deep learning. Experience in working with Arabidopsis and plant genome data is a strong plus. The position is expected to continue for multiple years
-
VwGr. B1 lit. b (postdoc) Limited until: 11.07.2030 Reference no.: 5864 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support
-
pursue the use of machine learning techniques for data analysis. Candidates must have a Ph.D. and research experience in experimental high energy physics. The successful candidate is expected to carry out