Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- France
- Germany
- Sweden
- United Kingdom
- Portugal
- Singapore
- Spain
- Italy
- Norway
- Netherlands
- Belgium
- Denmark
- United Arab Emirates
- Australia
- Poland
- Luxembourg
- Hong Kong
- Ireland
- Romania
- Austria
- Canada
- China
- Czech
- Japan
- Worldwide
- Bulgaria
- Cyprus
- Estonia
- Finland
- Malta
- Greece
- India
- Morocco
- Slovakia
- Switzerland
- Andorra
- Brazil
- Saudi Arabia
- Armenia
- Croatia
- Europe
- Israel
- Mexico
- New Zealand
- 35 more »
- « less
-
Program
-
Field
-
generalized parton distributions (GPDs). A key component of the PhD will also involve the development of novel algorithms designed to overcome current computational and theoretical challenges in hadron
-
otherwise be lost in the glare of their host stars. The primary goal of this PhD is to develop a novel active algorithm capable of achieving real-time starlight suppression across all wavelengths. The PhD
-
algorithmic, hardware, and platform engineering teams. What you will do You actively shape imec’s research and engineering roadmap by tackling the following core architectural challenges: Architecting endtoend
-
and optimising secondary prevention therapies, including:Drafting, testing and implementation of the clinical algorithm used in clinical practice to be implemented by the tool to assign a patient
-
contexts. Functions to be developed: Design, carry out theoretical analysis and experimental evaluation of graph protection algorithms, with the aim of guaranteeing properties such as privacy, security
-
enhancements, including advanced navigation algorithms, swarm intelligence, cyber security hardening, and payload-specific control systems. Key Responsibilities: Control Augmentation Development: Design
-
implementation of LED drivers for indoor lighting control. 2) Design of server management algorithms on an IoT server for monitoring light sensors and controlling the lighting system. Development of spectral
-
. AutoTraits is tackling a major bottleneck in crop development: slow, costly manual phenotyping. By combining cutting-edge algorithms with flexible, hardware-agnostic data capture, the project enables breeders
-
artificielle, en particulier des algorithmes d'apprentissage profonds, nous obtenons des modalités de plus haut niveau liées à l'actimétrie : la vitesse de déplacements voire certains mouvements corporels. Les
-
are open to hearing from candidates with a wide range of critically informed expertise. This includes but is not limited to expertise in critical approaches to algorithmic governance, AI and automation