142 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Nature Careers in Austria
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
2,900 work in administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate
-
from chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas
-
. The subject of the PhD should be within the areas of expertice of the laboratory for Cognitive Research in Art History ( https://crea.univie.ac.at/). Your future tasks: PhD thesis, preferably in
-
gases, radionuclides, or air pollutants. Our future research strategy also includes studies of the higher atmosphere. To learn more about our team, we invite you to visit our website: https
-
water-NanoSIMS assay), and process measurements. This is part of your personality: We are looking for a highly motivated candidate with an excitement and enthusiasm for soil microbiology and for learning
-
. Successful candidates will join a structured doctoral programme offering first-class supervision, vibrant research networks, and opportunities to publish, teach, and engage internationally.Candidates can
-
opportunities to publish, teach, and engage internationally.Candidates can select from a list of various open positions of supervisors in the participating doctoral schools (available on the Call website ). Your
-
and Master), and in two doctoral programs. Details on the department can be access on http://geographie.univie.ac.at/en/home/ . Your personal sphere of influence: The position is assigned to the working
-
of Europe.Successful candidates will join a structured doctoral programme offering first-class supervision, vibrant research networks, and opportunities to publish, teach, and engage internationally.Candidates can
-
human behavior in the usage of information technology. For this purpose, the group applies methods from reinforcement learning, explainable AI, natural language processing, and lab experiments