Researcher in “Generative Machine Learning”: We are seeking a motivated Researcher to join our team for a 36-month Fixed-Term Contract (FTC) as part of the TRACCS research program. The successful candidate will contribute to the development of statistical/machine learning approaches for down scaling climate variables at the kilometer scale. The position involves methodological development, learning strategy definition, and studying uncertainties in regional climate simulations.
Researcher in “Spatial High-resolution Climate Downscaling through Generative Machine Learning” (M/F)
Summary Table:
- Reference: FR636-AMISY-001
- Number of Positions: 1
- Workplace: GUYANCOURT
- Date of Publication: 14 May 2024
- Type of Contract: FTC Scientist
- Contract Period: 36 months
- Expected Date of Employment: 10 September 2024
- Proportion of Work: Full-time
- Remuneration: €3081.33 to €4291.70 gross monthly
- Desired Level of Education: Doctorate (Level 8)
- Experience Required: 1 to 4 years
- Section(s) CN: Earth System: Superficial Envelopes
Designation: Researcher
Research Area: Spatial High-resolution Climate Down scaling through Generative Machine Learning
Location: GUYANCOURT
Eligibility/Qualification:
- Doctorate in applied mathematics, climatology, or statistics with experience in machine learning.
- Essential technical skills in statistical modeling or machine learning, proficiency in R and/or Python, and knowledge in climate sciences.
- Preferred optional skills include experience with climate simulation data analysis, handling large datasets, and familiarity with NetCDF file format.
- Scientific English level B2 minimum.
Job Description: The Researcher will:
- Develop statistical downscaling and model emulation methods, focusing on machine learning approaches such as Generative Adversarial Networks (GAN).
- Design learning strategies and datasets for reliable local climate data production at high resolution.
- Study uncertainties in regional climate simulations and characterize various sources of uncertainty.
- Collaborate with TRACCS Core Project 6 on uncertainty quantification techniques.
How to Apply: Interested candidates should submit their application, including a CV and cover letter, to recruitment@email.com with the subject line “Application for Researcher in Spatial High-resolution Climate Downscaling”. Ensure that your candidate profile is correct before applying.
Last Date for Apply: 22 June 2024
Join us in contributing to cutting-edge research in climate modeling and make a significant impact on understanding and mitigating the effects of climate change.
