Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- France
- Portugal
- Germany
- Sweden
- Netherlands
- Spain
- Norway
- Belgium
- Denmark
- Italy
- Singapore
- Australia
- Finland
- Ireland
- Switzerland
- Luxembourg
- Czech
- Canada
- China
- Morocco
- Austria
- Estonia
- Poland
- Japan
- United Arab Emirates
- Hong Kong
- Brazil
- Malta
- Vietnam
- Andorra
- Macau
- Saudi Arabia
- Barbados
- Bulgaria
- Iceland
- Latvia
- Romania
- 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
- Linguistics
- Psychology
- Law
- Physics
- Electrical Engineering
- Social Sciences
- Sports and Recreation
- Education
- Design
- Philosophy
- 14 more »
- « less
-
NAME_FAMILY NAME) : https://nextcloud.univ-lille.fr/index.php/s/ezJxfSBwTjkJCnt Key words: solidification, recycled aluminum alloys, induction heating, thermal simulations, 3D modelling, mechanical testing
-
. The project combines interval timing and error monitoring in a novel behavioral task adapted to human and rat models. The leading hypothesis is a read-out model, which assumes that a Timer and a Reader are
-
. They will also lead the development of predictive distribution models that incorporate data from the experiment. The project is funded by the USGS CASC. Qualifications Required Qualifications: A completed
-
of large, cross-departmental initiatives. The analyst deploys data extraction, transformation, and loading (ETL) processes; classical statistical analysis; predictive and prescriptive modeling; optimization
-
. Viktar Asadchy[AALTO] Co-supervisors/mentors: Dr. Victoria Tormo [INDRA] and Dr. Barthès [3DEUS] Objectives To establish an analytical modeling approach for multilayer tunable metasurfaces that captures
-
extraction, transformation, and loading (ETL) processes; classical statistical analysis; predictive and prescriptive modeling; optimization; and data visualization techniques to generate actionable insights
-
Spanish and developing/testing computational models of second-language processing. The work is part of an NSF-funded project Predictive processing in naturalistic language comprehension through EEG and
-
, assess the health state of systems, and predict their future evolution and remaining useful life. The proposed approach integrates physics-based and data-driven modeling techniques, including machine
-
of hybrid foundation model-graph neural network architectures for gene perturbation prediction, including the design and implementation of novel training strategies under experimental constraints, e.g
-
to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large