Scientist for Machine Learning Development
vor 3 Wochen
We are seeking a highly skilled Scientist for Machine Learning to join our team at ECMWF. As a key member of our Earth System Modelling section, you will play a crucial role in developing cutting-edge machine learning applications to support future climate projections.
Our team is working on various projects, including the WarmWorld, EXPECT, and RAINA initiatives, which aim to develop novel machine learning models for weather and climate forecasting. You will have the opportunity to contribute to these projects and work closely with our team to develop and implement machine learning solutions.
The successful candidate will have a strong background in machine learning, deep learning, and scientific computing, with experience in developing and deploying machine learning models in large-scale environments. You will be responsible for adapting and extending existing machine learning models, implementing novel downscaling techniques, and training and optimizing machine learning models at scale.
We are looking for a dedicated and enthusiastic individual who is passionate about machine learning and its applications in climate modeling. If you are a team player with excellent communication and interpersonal skills, and a strong ability to analyze complex problems and develop innovative solutions, we encourage you to apply.
About ECMWFECMWF is a world-leading centre for weather and environmental forecasting, serving our members and the wider community with global weather predictions and data critical for understanding and solving the climate crisis. We are a 24/7 research and operational centre with a focus on medium and long-range predictions, holding one of the largest meteorological data archives in the world.
We are committed to having a diverse and inclusive workplace, and we welcome applications from nationals from ECMWF Member States and Co-operating States, as well as from all EU Member States. In exceptional cases, applications from nationals from other countries may be considered.
About the ProjectsThe WarmWorld project aims to develop the next generation of climate models and the required computational infrastructure for this, funded by the German federal ministry for education and research. The EXPECT project develops a prototype operational capability for integrated attribution and prediction of climate phenomena by exploiting novel data and technologies to provide trustworthy assessments and predictions of regional climate change including extremes, funded by the European Union through a Horizon project. The RAINA project aims to develop a statically robust, large-scale machine learning model for weather applications that supports a very fine, km-scale resolution.
Main Duties and Key ResponsibilitiesThe successful candidate will be responsible for:
- Adapting and extending existing machine learning models for climate modeling and forecasting
- Implementing novel downscaling techniques for climate data analysis
- Training and optimizing machine learning models at scale
- Collaborating with the project teams to develop and deploy machine learning solutions
We are looking for a highly skilled individual with a strong background in machine learning, deep learning, and scientific computing. The successful candidate will have:
- Excellent analytical skills to analyze complex problems and develop innovative solutions
- Excellent interpersonal and communication skills, and ability for efficient documentation and communication of scientific results
- Significant experience developing in Python or similar languages, and the use of software version control and best practices for software development
- Substantial experience with at least one deep learning framework (usually either PyTorch or JAX), in particular development and tuning of new architectures and training protocols
- Experience with the evaluation of machine learning applications and running of large ablation studies to determine optimal architecture hyperparameters
Education
- Advanced university degree (EQ7 level or above) in a computing, physical, mathematical or environmental science, or equivalent professional experience
Experience, Knowledge and Skills
- Experience in the general areas of machine learning and scientific computing
- Experience in machine learning and particular in machine learning model development
- Ability to deliver ready-to-use code
- Experience with generative machine learning and Earth system modelling is desirable
- Candidates must also be able to work effectively in English. A good knowledge of one of the Centre's other working languages (French or German) is an advantage
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