Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- France
- Portugal
- Germany
- Sweden
- Netherlands
- Norway
- Spain
- Belgium
- Denmark
- Italy
- Singapore
- Australia
- Finland
- Morocco
- Ireland
- Luxembourg
- Switzerland
- Canada
- China
- Poland
- Czech
- Austria
- Japan
- Estonia
- Hong Kong
- Brazil
- United Arab Emirates
- Vietnam
- Andorra
- Macau
- Malta
- Saudi Arabia
- Slovakia
- Barbados
- Bulgaria
- Iceland
- Latvia
- Slovenia
- 30 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Materials Science
- Mathematics
- Earth Sciences
- Chemistry
- Environment
- Business
- Humanities
- Arts and Literature
- Psychology
- Law
- Linguistics
- Physics
- Social Sciences
- Electrical Engineering
- Sports and Recreation
- Education
- Design
- Philosophy
- 14 more »
- « less
-
to the weather prediction and climate projections. This is mainly due to our lack of understanding of cloud/snow ice microphysics and over-simplified representation in models. On a broader sense, although weather
-
model biases, and identify sources of predictability. The project will involve; 1) rigorous interrogation of NOAA GFDL's CM4X simulation output with respect to coastal sea level variability and relevant
-
), multimodal vision and language models, and Large Language Models. Please find prior work here: (Google Scholar: https://scholar.google.com/citations?hl=en&user=oEifmSgAAAAJ&view_op=list_works&sortby=pubdate
-
they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale
-
physics-integrated machine learning models—to predict, analyze, engineer, and understand microbial community dynamics. Applications span precision medicine and built environment microbiomes, with a strong
-
to develop an aeromedical dispatch management software as a technology hub that provides data-driven prediction model and an automated dynamic decision model. The successful candidate will be responsible
-
and machine learning based analyses including predictive modeling and real world evidence generation. Basic Qualifications: MS in computer science, biostatistics, biomedical informatics or related field
-
modeling to create a predictive tool that spans orders of magnitude in length and time. Hands-On Numerical Modeling: Implement your model in a custom-made data analysis tool that uses advanced optimization
-
cancer therapeutics and biomarker development to strategically develop our portfolio of preclinical cancer models and ex vivo approaches. Your goal is to enhance our mission to validate and credential new
-
Computational modelling of two-dimensional graphene-based materials School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Natalia Martsinovich Application Deadline