Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Sweden
- Germany
- Netherlands
- Spain
- Portugal
- France
- Singapore
- Norway
- United Arab Emirates
- Denmark
- Belgium
- Switzerland
- China
- Australia
- Poland
- Austria
- Italy
- Luxembourg
- Finland
- Hong Kong
- Canada
- Morocco
- Vietnam
- Ireland
- Romania
- Czech
- Japan
- Estonia
- Greece
- Brazil
- Saudi Arabia
- Croatia
- Lithuania
- South Africa
- Andorra
- Cyprus
- India
- Taiwan
- Malta
- New Zealand
- Slovenia
- Worldwide
- Israel
- Kenya
- Latvia
- 37 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Mathematics
- Education
- Psychology
- Materials Science
- Earth Sciences
- Chemistry
- Arts and Literature
- Environment
- Social Sciences
- Humanities
- Linguistics
- Electrical Engineering
- Sports and Recreation
- Law
- Physics
- Philosophy
- Design
- Statistics
- 15 more »
- « less
-
to analyze data and experience with statistical, machine learning, and data science approaches. Prior experience working in teams on collaborative projects. Knowledge, Skills and Abilities: Expertise in one
-
: Education: Bachelor in Biosciences, or Engineering degree in Computer or Data Sciences. PhD in bioinformatics, data sciences, machine learning or related areas. Experience: previous experience working with
-
). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
-
Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP) | Paris La Defense, le de France | France | about 2 months ago
a postdoctoral researcher to work full-time on the DiscoReel project. The postdoc will work on developing machine and deep learning methods for epidemic modeling, integrating them with mechanistic
-
large-sample hydrology (LSH) datasets, deep learning rainfall-runoff models, and hydrological alteration analyses, with the ultimate goal of improving the identification and management of ecological flows
-
datasets Implement LLM and Machine Learning algorithm Conduct statistical analysis in SAS or Stata Assistant with other ad hoc tasks Required Education Bachelor’s or Master’s degree in computer science
-
comparative insights that enhance research conclusions from Hope observations. Develop Machine Learning methods and run numerical simulations on NYUAD’s High-Performance Computing (HPC) system. Support
-
, computational biology, or bioinformatics with a heavy focus on machine learning and AI model training and development by the appointment start date. About 1 year of research or work experience in an academic
-
). Applying advanced statistical and machine learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development
-
simulations with machine learning models derived from experimental data. 1) Functional Knowledge and Technical Expertise (50%) a. COMSOL Modeling: Design, build, and run COMSOL Multiphysics simulations to model