Sort by
Refine Your Search
-
Country
-
Employer
-
Field
-
and its implementation in distributed systems. Main responsibilities: Research, develop, and optimise machine learning algorithms, including deep learning, for AV control and coordination. Apply multi
-
We are recruiting an Artist in Residence to undertake artistic research with a focus on Distributed Acoustic Sensing (DAS) technology, in the context of the recently awarded UKRI grant ‘SOUNDSCALE
-
, distributed algorithms, secure multiparty computation, and information theory. You are expected to speak and write in English at an academic level, and preferable also in Danish. Qualification requirements
-
100%, Zurich, fixed-term The Distributed Computing (DISCO) Group is a research group at ETH Zurich, led by Prof. Dr. Roger Wattenhofer . We are interested in a variety of research topics on new and
-
proficiency in distributed and high-performance machine learning algorithms, methods for exploiting modern system architectures for high-performance AI, and quantum distributed computing. A proven track record
-
expertise in distributed and high-performance systems, you will be able to display proficiency in distributed and high-performance machine learning algorithms, methods for exploiting modern system
-
AI-enabled digital technologies for the resilient operation of power systems School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Xin Zhang Application Deadline
-
Prof Lyudmila Mihaylova Application Deadline: Applications accepted all year round Details This research project focuses on the development of methods for intelligent wildfire detection and localisation
-
you will do Driving innovative AI research through the development and implementation, practical application, theoretical analysis and evaluation of AI algorithms Use of XAI tools to explain machine
-
for monitoring people’s health. You will focus on developing new solutions, electronics, algorithms and methods to assist individuals, physicians and sports coaches to effortlessly and continuously monitor health