Research fellow positions - 2022

Research agenda

Projects and positions

At this moment we have open research positions (both PhD and postdoc) to work on machine learning and explainable AI in the following European Space Agency (ESA) projects:

1. ESA DeepExtremes – AI4Science: Multi-Hazards, Compounds and Cascade events [1 postdoc, 1 PhD]

Deep learning eXplainable AI Geosciences/climate
Application form: here
Enquiries: Prof. Gustau Camps-Valls
Climate extremes are on the rise. This is one of the most critical manifestations of climate change as extreme events have multiple impacts: from declining ecosystem functioning associated with reduced ecosystem services e.g., carbon sequestration and water retention, to harvest failure with very direct impacts on human wellbeing. In the last few years, it has been recognized that the highest threats on ecosystems and societies are due to multi-hazard events. Such events may translate into “compound events”, which often do not only affect one particular land-surface process but rather induce entire cascades of consequences. In the project we will rely on deep learning to deal with spatio-temporal data, techniques from computer vision for forecasting impacts, and the advanced regression methods for associating impacts on biosphere and society. Understanding what the DL models have learned are of importance here, so experience on explainable AI (XAI) techniques and methods from modern Bayesian inference (Bayesian deep learning and deep GP regression) to perform uncertainty quantification, automatic variable relevance determination, and error propagation are pluses.

This is a joint collaborative project between four outstanding partners: The University of Leipzig (led by the group of Prof. Mahecha, RSC4Earth), the Max Planck Institute for Biogeochemistry (led by Prof. Reichstein, MPI-BGC), Brockmann Consult, and the Universitat de València (led by Prof. Camps-Valls, ISP). The successful candidate will be based in the Universitat de València, but will actively collaborate and visit the other groups and ESA (Frascati).

2. ESA OpenSR – Towards Explainable AI: Application to Trustworthy Super-Resolution [1 postdoc, 1 PhD]

Deep learning eXplainable AI Super-Resolution
Shared research position between University of Valencia (Spain) and University of Oxford (UK)
Application form: here
Enquiries: Prof. Luis Gómez Chova or Prof. Freddie Kalaitzis
The OpenSR project aims to bring robust, accountable, and scalable multi-spectral super-resolution techniques to the Earth Observation (EO) community for the ubiquitous L2 and L3 pre-processing of the Sentinel-2 (S2) revisits archive. Super-resolution (SR) is a nascent technology and the roadmap to maturity will require insights from many disciplines. Super-resolution is not just about image generation, but also degradation: how much information is lost in pixelation. To shift the public perception on the safety of SR-S2 products, we will provide uncertainty and quality metrics along with the new SR products; establish and disseminate best practices through our new methods and tools that will be open to everyone.
We offer a PhD and a postdoctoral research fellow position to work on Multi-Image Super-Resolution and Explainable AI with Sentinel-2 satellite images in a European Space Agency (ESA) collaborative project between our two research groups.

The successful candidate will be based in the University of Valencia, Valencia, Spain, and will be supervised by both Dr. Freddie Kalaitzis, at the University of Oxford (OATML), and Dr. Luis Gómez Chova, at the University of Valencia (ISP). This will imply frequent teleconfs, possibility of teleworking, and eventual stages at the University of Oxford. This will not be a solo research project, like typical postdoc or PhD projects, but more in line with a collaborative effort occurring in an industrial setting. This is an opportunity to hone team skills while collaborating with a team of researchers (another research fellow and the principal investigators). More info here.

Your Profile

  1. Experience in machine learning, deep learning, image processing, statistics, Bayesian inference
  2. We love interdisciplinarity! Interested in remote sensing, Earth sciences, climate science
  3. Experienced in scientific interpretation and analysis of data
  4. Experienced with or convincing motivation to enter a leadership position
  5. Familiar with modelling, model-data-fusion and machine learning
  6. Excellent quantitative skills (e.g. data analysis, modelling)
  7. Strong programming skills in Python/Julia/R
  8. Proven record of scientific publications in international peer-reviewed journals
  9. PhD in maths, physics, or computer science
  10. Critical and organized sense for data analysis
  11. Maturity and commitment
  12. Strong communication, presentation and writing skills are a big plus
  13. Collaborative team player

Your tasks

  1. Lead research along the project specific topics
  2. Collaborate with a team of researchers
  3. Co-advise PhD students
  4. Publish in international peer-reviewed journals and conference venues

Why ISP? Context and offer

The successful candidates will be based in the Universitat de València, Spain. Prof. Camps-Valls is the coordinator of the Image and Signal Processing (ISP) group. The group is devoted to the development of machine learning and signal processing techniques for remote sensing image processing, Earth observation data analysis and the Geosciences. Several topics are treated in our research group and projects: regression, causality & information theory, Earth observation data analysis, physics-aware machine learning, generative modeling, eXplainable AI and feature ranking, and anomaly detection. The ISP group is the place to be:
  1. Truly interdisciplinary projects: machine learning + climate/geo sciences + neuroscience + socio-economics
  2. Work in cutting-edge machine learning to tackle relevant, challenging societal, environmental and climate problems
  3. Postdocs may supervise outstanding students and lecture in top EU master is possible, yet not mandatory.
  4. Access to high performance computing facilities and clusters
  5. Part-time job and teleworking are generally acceptable
  6. Flexibility to work on side projects with companies and international organizations (see list of collaborators)
  7. We care about diversity and the gender issue!
  8. Active group, engaged in vibrant AI networks like ELLIS, i-AIDA and ESA PhiLab and with cool collaborators
  9. Very friendly, interactive and international working environment
  10. Salary according to UV scales + health insurance + travel money. Excellent cost-of-living index = 55