Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- University of Utah
- Imperial College London
- UNIVERSITY OF HELSINKI
- ; University of Cambridge
- AALTO UNIVERSITY
- Duke University
- Ghent University
- Leibniz
- Nature Careers
- SINTEF
- University of California Irvine
- University of Cambridge
- University of Florida
- University of Lethbridge
- University of Newcastle
- University of Tübingen
- 6 more »
- « less
-
Field
-
Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
-
statistical models (for example principal component analysis) to obtain insights into relationships between physical properties of polysaccharides (composition, molecular weight charge, chain length etcetera
-
will develop and apply cutting-edge methods in predictive and causal modeling for age-related macular degeneration (AMD), a primary cause of irreversible vision loss worldwide. This work will involve
-
effect can be predicted. You will acquire in-situ and remote-sensing data of cirrus forming downwind of flights over the past decade, along with measurements/estimates of local conditions and emissions
-
complementary methodologies (corpus data and offline experimental measures). On the theoretical side, the project will develop a formal compositional model that generates the observed parameters of variation and
-
are linked to research on composite hydrogen tanks, composite propellers for drones and finite element modelling of textile manufacturing. All research will be conducted with leading companies in
-
models. This theoretical project will facilitate close collaboration with experimental groups and enable benchmarking of theoretical predictions. The PhD researcher will be part of the Correlated Quantum
-
validating deep learning models for the prediction of disease progression from ophthalmic data. Skills include working with image or computer vision-based toolkits, development of multimodal, multidata type
-
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
-
will develop andapply cutting-edge methods in predictive and causal modeling for age-related maculardegeneration ( AMD ), a primary cause of irreversible vision loss worldwide. This work willinvolve the