Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
, DeepFields (using drones, airborne optical sectioning (AOS) -a unique synthetic aperture sensing technique developed by JKU-, and machine learning for harvest and damage estimation in agriculture), in
-
Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | 10 days ago
, Approximation Theory, Machine Learning, Inverse Problems and Regularization Theory. Proficiency in programming with a strong preference for Python and deep learning frameworks such as PyTorch is highly desirable
-
11 Mar 2026 Job Information Organisation/Company Johannes Kepler University Department Institut for Machine Learning Research Field Computer science Researcher Profile Recognised Researcher (R2
-
the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists
-
preferred Excellent knowledge of microeconometric methods for causal inference; knowledge of machine learning methods is preferred Experience in university teaching Strong communication and teamwork skills
-
explicit model of the biophysical effect of land use change, a machine learning emulation of dynamic global vegetation models. Both activities aim to improve understanding and quantification of the effects
-
, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7
-
of machine learning What We Offer: On the basis of full-time employment (40 hours/week) the minimum salary in accordance with the collective agreement is € 5,014.30 gross per month (14 x per year, CA Job Grade
-
(https://oskar-morgenstern-doctoral-school.univie.ac.at/), providing them with additional funding for research, and the possibility to learn from and with students from adjacent disciplines. Outside
-
the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists