Postdoctoral Research Fellow in Machine Learning and Data Science for Climate Science
The Cyprus Institute
The Cyprus Institute (CyI) is a European Non-profit Science and Technology oriented Educational and Research Institution based in Cyprus and led by an acclaimed Board of Trustees. The research agenda of the CyI is pursued at its four Research Centres:
- The Computation-based Science and Technology Research Centre (CaSToRC),
- The Science and Technology in Archaeology and Culture Research Centre (STARC),
- The Energy Environment Water Research Centre (EEWRC) and
- The Climate and Atmosphere Research Centre (CARE-C).
Considerable cross-centre interaction is a characteristic of the Institute’s culture.
The Cyprus Institute is an Equal Opportunities Employer certified from the Cypriot Ministry of Labor and also an HRS4R accredited Institution that adheres to the European Commission’s “Charter & Code” principles for recruitment and selection.
Climate: Past, Present & Future (CL)
Earth and Space Science Informatics (ESSI)
The Cyprus Institute invites applications for a highly qualified and motivated individual to join the Institute as a Postdoctoral Research Fellow in Machine Learning and Data Science for Climate Science in CaSToRC. The successful candidate will apply Machine Learning for investigating key processes of the Earth System, including (but not limited to) the following:
- Extreme event (weather, temperature, precipitation, etc.) risk detection
- Data-driven and hybrid modeling of the Earth system
- Using machine learning to develop new parameterizations for climate models
- Causal inference in the context of climate change
- Machine learning in support to air quality modelling for exposure mapping, super-resolution, short-term forecasts and long-term projections
This position offers a unique opportunity for fundamental research and its exact focus will be determined also based the interests and skills of the successful candidate. The successful candidate will also work closely with the PIs in writing relevant grant proposals.
The appointment is for a period of 2 years, with the possibility of renewal subject to performance and the availability of funds. An internationally competitive remuneration package will be offered, which is commensurate with the level of experience of the successful candidate.
Responsibilities/activities to be involved in:
- Development of novel Machine Learning/AI models for the analysis of climate phenomena
- Collection and statistical analysis of observational and model data relevant to atmospheric and climate change, with a special focus on the Eastern Mediterranean and the Middle East (EMME)
- Writing Research Papers in collaboration with the PIs – aiming to publish at top-tier conferences and journals
- Presentation of results in conferences and meetings and participation in journal publications
- Contribution to research proposal preparation, project (scientific) reporting & project management
- Supervision and guidance of Research Assistants and Students
- PhD in computer science, geosciences, physics or a related field (such as computational science, applied math or climate science) at the time of the appointment (The candidate must hold a PhD degree of a recognized higher education institution before the deadline of the opening. Candidates who have successfully defended their doctoral thesis but who have not yet formally been awarded the doctoral degree will also be considered eligible to apply provided that they can document their successful defense of the thesis)
- Publications in the areas of Artificial Intelligence and/or Machine Learning (either developing new methods in these areas — or applying existing methods in climate science)
- 3 year-experience (including PhD research)
- Understanding of fundamental concepts in climate science
- Proficient programming skills (preferably in Python) and experience with deep learning frameworks such as PyTorch
- Ability to work as part of an interdisciplinary team while showing initiative and independence
- Excellent knowledge of the English language (written and verbal)
- Experience with statistical methods for climate datasets
- Background in atmospheric dynamics, climate modeling
Applicants should submit a curriculum vitae including a short letter of interest, list of publications and a list of three (3) referees (including contact information). All documentation should be in English and in PDF Format. Please note that applications which do not fulfill the required qualifications and do not follow the announcement’s guidelines will not be considered.
For further information, please contact Prof Constantine Dovrolis