Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- France
- Germany
- Sweden
- United Kingdom
- Portugal
- Singapore
- Norway
- Spain
- Italy
- Netherlands
- Belgium
- Denmark
- Poland
- United Arab Emirates
- Australia
- Luxembourg
- Romania
- Ireland
- Canada
- China
- Hong Kong
- Austria
- Czech
- Finland
- Worldwide
- Cyprus
- Estonia
- Japan
- Malta
- Switzerland
- Greece
- India
- Morocco
- Slovakia
- Andorra
- Bulgaria
- Saudi Arabia
- Armenia
- Brazil
- Europe
- Mexico
- New Zealand
- 33 more »
- « less
-
Program
-
Field
-
. Kurusch Ebrahimi‑Fard and is connected to the research activities of the national project SURE‑AI. The PhD project focuses on developing mathematical and computational methods based on path signatures and
-
to integrate large and complex preference datasets with information at individual level, with specific attention to open and reproducible research, e.g., in the development of codes and algorithms. We will focus
-
National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
-
, towards a common goal of transforming the diagnostics and preservation of cultural heritage by developing innovative non-destructive evaluation techniques and advanced digital tools for diagnostics
-
/08/2025 END: 31/12/2029 Centre of Principal Researcher: Faculty of Computer Science. Álvaro Leitao Rodríguez PURPOSE OF CONTRACT: Advanced Deep Learning algorithms for solving PDEs and SDEs in finance
-
-modal”) neural + behavioral disease-state models. The purpose of the research project(s) this position supports: The purpose of the research supported by this position is to develop a computational
-
graduate students, etc. In particular, the MLE hired for this position will work with Ayan Paul and Hyunju Kim at EAI and is expected to develop AI algorithms for drug synergies with a combination of public
-
FLEX/FFPE), ATACseq, nCounter panels, spatial transcriptomics, ChIP-seq, cut-and-run and others Apply machine learning algorithms to clinical multi-omic datasets. Assist with collaborative and service
-
these interactions and their evolution are studied, with a few privileged fields that are particularly sensitive to these interactions, whether local or global. Each of these socio-ecosystems is used as a laboratory
-
cylinder flow. Journal of Fluid Mechanics, 896, A24. Your research program After getting familiar with the existing mathematical formalism and numerical tools, you will develop new algorithms to efficiently