Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Sweden
- United Kingdom
- Germany
- France
- Norway
- Portugal
- Singapore
- Belgium
- Spain
- Netherlands
- Denmark
- China
- Italy
- Australia
- Switzerland
- Luxembourg
- Canada
- Hong Kong
- United Arab Emirates
- Austria
- Finland
- Czech
- Morocco
- Poland
- Ireland
- Cyprus
- Japan
- Brazil
- Latvia
- India
- Saudi Arabia
- Lithuania
- Bulgaria
- Estonia
- Greece
- Taiwan
- Andorra
- Israel
- Romania
- Slovenia
- South Africa
- Armenia
- Barbados
- Europe
- Iceland
- Malta
- Mexico
- New Zealand
- Slovakia
- Vietnam
- 41 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Education
- Mathematics
- Psychology
- Materials Science
- Arts and Literature
- Humanities
- Social Sciences
- Chemistry
- Linguistics
- Earth Sciences
- Environment
- Law
- Sports and Recreation
- Electrical Engineering
- Physics
- Philosophy
- Design
- 14 more »
- « less
-
remain poorly understood. Their structural heterogeneity and chemical complexity make accurate atomistic modeling particularly challenging. Recent advances in machine learning approaches provide a powerful
-
on correlation-based machine learning. When an agricultural system fails due to compounding climate extremes - like a simultaneous heatwave, drought, and ozone pollution spike - standard models can forecast the
-
. Desirable Criteria Experience implementing machine learning or deep learning models (e.g., neural networks, probabilistic learning methods). Knowledge of state estimation techniques, such as Kalman filters
-
on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
-
Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 25 days ago
independently; and ability to work as part of a tightly-knit team. PREFERRED: Experience with theoretical analysis, using and building machine learning models, and developing circuit models. 3/16/2026
-
the foundational mathematics and programming skills necessary for creating basic neural networks and deep learning models from the ground up. Additionally, it is designed for those keen on comprehending
-
Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming tools such as R packages, Phyton, and other programming languages Publications in the field Excellent
-
(HAC). This role focuses on applying advanced computational and analytical methods—including artificial intelligence, machine learning, deep learning, time-series modeling, and large language models
-
quantitative discipline or equivalent experience. · Experience applying statistical or machine learning methods in real-world contexts. · Proficiency in Python and/or R for data analysis and modelling. · Strong
-
Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a