135 computational-physics "https:" "https:" "https:" "https:" "Trinity College, Dublin" positions at Aarhus University in Denmark
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
decomposed into modular sub-components that can be either process-based models and/or deep learning models. MCL has the flexibility to replace any uncertain process description with a deep learning model
-
level, e.g. in medical physics, physics, biomedical engineering or computer science. It is mandatory that your PhD degree is on a topic relevant for this specific position, e.g. in medical image-based
-
in the fields of: Construction Management and Lean Construction. Production Planning and Control. Data-driven analytics and management of construction operations. Construction Informatics, including
-
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
-
candidates will be involved in materials crystallography research in collaboration with other members of the Iversen group. The candidates must have a PhD in chemistry, crystallography, physics, materials
-
advice, and education. We offer professional laboratories, greenhouses, semi-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international
-
, the position entails developing, organizing, and teaching the equivalent of one MA course per year as part of the Political Science program at Aarhus University. Your qualifications Applicants are expected
-
Experience in planning and conducting field-work Experience in planning and conducting laboratory work within nitrous oxide field measurements, soil sampling and the quantification of soil physical, biological
-
developments within the field, including plans for publications, funding applications and collaborations with external partners. Please note that although the application process can be completed in the Aarhus
-
description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will