Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
enabling trustworthy AI adoption through methods and tools for compliance, readiness, and performance evaluation. In the field of Smart Cities, we lead the operations of the CitCom.ai project. CitCom.ai is
-
maintain scalable and high-performance software solutions Implement frontend applications using a modern JavaScript framework (React or Vue.js) Containerize applications using Docker for consistency across
-
Europe, and contributing to innovations that enhance healthcare and medical research. As part of the IDERHA development team, you will: Design, develop, and maintain scalable and high-performance software
-
with high dimensionality: Computational difficulties linked to the high dimensionality of the underlying tensor approach have been tackled in [GOU20] by undersampling the measured AF ECG signals
-
the general management of LIH in order to guarantee scientific excellence of the research work performed in the department by providing scientific advice and guidance to the Principal Investigators
-
computational approaches. We are seeking a postdoctoral researcher to: Perform research on Parkinson's disease by the use of iPSCs Characterize molecular impairment in PD Become an active lab member For further
-
Keywords Digital twin, signal processing, AI, operating room, risk management, healthcare improvement. Context Surgery represents a strategic area for improving practices with high potential
-
mathematics for Grade 1 in the frame of the Luxembourgish School Monitoring Programme - Épreuves Standardisées (ÉpStan). At LUCET, you will work in a collaborative and research-driven environment, contributing
-
Virtual laboratory to predict the ability of a fluctuating biomass to satisfy a material use-VARIOUS
. The starting point will be the microstructural databases of the BIA where different properties (tissue structure, cellulose content) will serve to establish scalar links to predict very early the performance and
-
, copyrighted, or biased. By studying brain data recordings and building computational models that mimic real populations of neurons, the project aims to uncover active unlearning: how the brain learns