Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- ;
- University of Utah
- DAAD
- Duke University
- Imperial College London
- University of British Columbia
- University of Cambridge
- Wayne State University
- ; Technical University of Denmark
- ; University of Cambridge
- AALTO UNIVERSITY
- California Institute of Technology
- Ghent University
- ICN2
- Leibniz
- Technical University of Denmark
- Temple University
- The Ohio State University
- University of California Irvine
- University of Lethbridge
- University of Luxembourg
- University of Oslo
- University of Pittsburgh
- University of Tübingen
- Université libre de Bruxelles (ULB)
- 15 more »
- « less
-
Field
-
, comparing results with theoretical predictions to assess data quality. Technical Documentation: Prepare detailed reports and contribute to scientific publications. Operates, maintains, and troubleshoots
-
the impact of molecular rearrengements on the performance, shelf lifetime and stability of electronics. Our goal is to define a physical framework capable to predict relevant timescales.The successful
-
measurement campaign using high-speed imaging and in-line force measurements on actual textile manufacturing machinery in collaboration with leading industrial partners. The goal is to develop a predictive
-
One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
-
. The sub-project of the Phytophotonics department focuses on analysing hyperspectral imaging data for predicting infestations in field crops. The focal topics of the sub-project include: Realisation of a
-
. The areas of responsibility include: Develop computer vision and AI models for detecting wind turbine blade damage and predicting its progression, with experimental validation carried out at DTU test
-
) to discover multi-modal biomarkers, immune-microbe interaction modules, and spatially localized signatures associated with disease outcomes. • Develop novel AI-driven frameworks to predict clinical phenotypes
-
, perform cutting-edge analytical techniques for causal inference and prediction, and writing papers for both an academic audience and for practitioners (managers and/or policymakers). Desired Qualifications
-
Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
-
position is funded by multiple NIH projects, e.g., https://tinyurl.co m/ysxhmujvThe overall goal is to : (1) develop inference and dynamic prediction models using a wide variety of data, including clinical