Doctoral Candidate In Computer Vision And Machine Learning For Developing Novel
Vollzeit @Universität Zürich veröffentlicht 1 Tag agoJob-Beschreibung
Your responsibilities
The successful candidate will work on a project in the EcoVision Lab in cooperation with colleagues at Empa and Wageningen University on developing novel deep learning methods for satellite-based tracking of global CO2 and NOX emissions of point sources (STEPS).
The next generation of polar-orbiting CO2 satellites will provide images of CO2 and NO2 emission plumes from point sources with unprecedented accuracy, resolution and coverage. The combination of CO2 and NO2 measurements will thus enable the long-term monitoring of the emissions from large point sources across the globe, which will be critical for tracking progress in reducing air pollution and achieving net-zero emissions under the Paris Agreement. The vast number of images acquired by the next generation of satellites and the large number of observable sources requires automated emission quantification methods based on deep learning.
STEPS will advance deep learning models to quantify CO2 and NOX point source emissions from CO2 and NO2 imaging satellites. The project will generate and publicly release an unprecedented library of highly realistic, globally representative satellite images based on high-resolution chemical transport simulations. The deep learning models will then be adapted to real satellite imagery to minimize the domain gap. Once developed and tested, the novel methods will be applied to the next generation of polar and geostationary satellites to monitor the CO2 and NOX emissions from power plants and industrial facilities. The STEPS project will establish an advanced framework to develop, validate and apply deep learning models for emissions quantification.
The project leaves ample room to explore various exciting technical avenues like self-supervised learning, physics-informed deep learning, uncertainty quantification, interpretability, and explainability in deep neural networks, attention-based approaches, or diffusion models, for example. Over course of the project, publications are planned at both, machine learning and computer vision conferences like CVPR, ICCV, ICLR, NeurIPS and journals like Remote Sensing of Environment, the ISPRS Journal or Nature Sustainability.
Your profile
We are looking for candidates with an interest in performing innovative research, strong motivation, and an interest in software development. An ideal candidate will have:
- an excellent degree (. or equivalent) in Computer Science, Machine Learning, or a related field (e.g. Electrical Engineering, Applied Mathematics, Physics)
- strong understanding of maths and physics
- experience in programming, preferably in Python
- prior experience in machine learning, computer vision and remote sensing and strong interest to apply these skills to an interdisciplinary project
Furthermore, the candidate should be fluent in English, both written and spoken.
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Location
Department of Mathematical Modeling and Machine Learning (DM3L)
Information on your application
Please submit your complete application (motivation letter, curriculum vitae, school and university score records, contact details of at least two referees) via the link below. The deadline for applications isand the desired starting date isSelection will start immediately, so early submissions are encouraged.
Further information
Questions about the job
Prof. Jan Dirk Wegner
Professor
Working at UZH
The University of Zurich, Switzerland’s largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education. Put your talent and skills to work with us. Find out more about UZH as an employer!
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