43 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr"-"Newcastle-University" positions at Aarhus University
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
-
at the Department of Mathematics. The academic content of the program is identical to that of the already existing bachelor's program in Data Science, but all teaching is conducted in English, and the recruitment is
-
The Department of Biomedicine at Faculty of Health at Aarhus University invites applications for a position as an academic employee within image analysis and IT infrastructure for imaging data as
-
Mechanics and Turbulence” group and conduct research on data-driven techniques for turbulence modeling in LES and RANS. The initial contract will be for one year, with the possibility of an additional one
-
various data analysis tasks. Your work will focus on carrying out data preprocessing, data wrangling, and carrying out analyses using R (and sometimes Python). Example projects you will be working
-
unified data framework for microbial carbon dioxide conversion, integrating data from methanogens, acetogens, and hybrid projects for standardization, kinetic/thermodynamic measurements, and predictive
-
As research assistant, your primary tasks are full time laboratory work and data analysis. You contribute to the development of the department through research of high international quality. In your
-
in the fields of: Construction Management and Lean Construction. Production Planning and Control. Data-driven analytics and management of construction operations. Construction Informatics, including
-
underlying greenhouse gas fluxes Support training of young researchers in using biogeochemical observations and data analysis Write and contribute to international peer-reviewed publications Contribute
-
will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental