13 data-"https:"-"https:"-"https:"-"https:"-"Cyprus-University-of-Technology" positions at Empa
Sort by
Refine Your Search
-
of Zurich and Wageningen University & Research. The four-year STEPS project focusses on developing data-driven and machine learning methods to monitor CO2 and NOx emissions using the upcoming satellite
-
to support a circular bioeconomy. We are seeking a highly motivated postdoctoral researcher to develop and apply machine‑learning and data‑science methods, with a focus on computer vision, to enhance wood
-
interdisciplinary project on the development of new computational approaches for improving safety and sustainability of (nano)materials based on publicly available data and tools, including omics data, and
-
. Please submit these exclusively via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2025/phd-position-in-data-driven
-
-based optimization, enabling autonomous measurement campaigns and real-time data assimilation. This research combines fluid mechanics, artificial intelligence, and robotics to establish the foundation
-
and coordinate generation of new datasets for the scientific problems of interest. Analyse the data, write scientific manuscripts and present results at international conferences. Your profile Required
-
models and in vitro assays. Experience in phototherapy, programming and large data analysis is a plus. Excellent communication skills and fluency in English (written and oral). Our offer The project is
-
, based on measured air temperature and humidity data in cold chains by commercial sensors, and deploy them in end-to-end virtual supply chains. This project also aims to optimize other thermal processes
-
types of textiles Data management, data treatment Reporting and publication Your profile If you are interested in making a major impact on functional clothing and textiles, are highly motivated and
-
components and nucleic acids interact and self-assemble. Apply data analysis and modeling to deepen understanding of nanoparticle architectures, and contribute to standardization-relevant method development