Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Norway
- Sweden
- France
- Belgium
- Netherlands
- Denmark
- Portugal
- Spain
- Singapore
- Australia
- Hong Kong
- China
- Austria
- United Arab Emirates
- Poland
- Switzerland
- Canada
- Luxembourg
- Ireland
- Italy
- Czech
- Estonia
- Finland
- Latvia
- Romania
- Cyprus
- India
- Andorra
- Morocco
- South Africa
- Lithuania
- New Zealand
- Brazil
- Croatia
- Saudi Arabia
- Slovenia
- Worldwide
- Armenia
- Israel
- Japan
- Barbados
- Bulgaria
- Europe
- Greece
- Iceland
- Indonesia
- Malta
- Qatar
- Slovakia
- Taiwan
- Vietnam
- 44 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Engineering
- Biology
- Economics
- Science
- Mathematics
- Chemistry
- Business
- Social Sciences
- Arts and Literature
- Materials Science
- Psychology
- Humanities
- Education
- Linguistics
- Electrical Engineering
- Environment
- Earth Sciences
- Law
- Physics
- Design
- Sports and Recreation
- Philosophy
- Statistics
- 15 more »
- « less
-
Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 23 days ago
will focus on the following main tasks: 1) Machine-learn optimal reaction coordinates for the barnase-barstar complex, starting from ~0.1 millisecond high-dimensional MD (generated by a previous PhD
-
qualitative and quantitative analytical methods to model clinician attention, verbal reasoning, and documentation behaviour Develop and evaluate machine learning models, including unimodal, fusion, and
-
the use of machine learning and AI approaches • Integration of proteomics with genetic data via MR, coloc and FUSION to identify causal and druggable targets Requirements • The successful applicant will
-
have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants are expected to demonstrate research experience in the fields of structural modeling and machine-learning
-
background, you may be considered if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme https
-
an increased interest in adapting and developing the latest machine learning methods for the purpose of malware detection, and preliminary results are encouraging. The specific goals of this project include
-
the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
-
vision, XR and generative models, specifically for capturing challenging scenarios and training deep learning systems to create better experiences for human users and learners. You will contribute
-
comprehensive platform for data extraction, analysis, and version control, providing access to highly curated datasets in a machine learning-friendly format. This PhD is part of the CARES project (Chemically
-
master’s degree with academic qualifications in digital health, data analysis, and/or machine learning applied to health research. Admission to the PhD program requires a 120 ECTS master’s degree, including