Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
to interact and collaborate to develop robust ways to decode single molecule imaging data. Your profile The candidate should hold a PhD in biophysics, chemistry, nanoscience or related subjects and have a
-
is expected to hold a PhD degree relevant to the topics of the fellowship. Such a degree might be in (Medical) Sociology, Public Health, Epidemiology, or another area related to survey data analysis
-
hold a PhD in oceanography, marine ecology, computer sciences, data sciences or similar. We expect that you have: Expert knowledge on network modelling, especially aimed at ecological applications Strong
-
learning–based), advanced mesh generation techniques for simulation, and experience with biomedical simulation, both virtual and physical. Experience with laboratory and clinical validation of models is
-
of strains) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modelling
-
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
-
). Applicants should have completed their PhD in Finance or a related area prior to starting. We also encourage seasoned candidates with a strong research pipeline and teaching experience to apply. Job
-
inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
-
sluice, which will then be used in a learning framework to design an automatic controller to optimize the usage of the sluice under various conditions. The other project will address challenges related
-
the department We seek a candidate with the following qualifications : Required: PhD in wildlife ecology, conservation biology, or a related field Experience with technology-assisted wildlife monitoring (e.g