The Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI) is a member of the Helmholtz Association (HGF) and funded by federal and state government. AWI focuses on polar and marine research in a variety of disciplines such as biology, oceanography, geology, geochemistry and geophysics thus allowing multidisciplinary approaches to scientific goals.
Postdoc in deep learning for atmospheric science foundational modelling (m/f/d)
Background
The use of deep learning for weather forecasting has exploded in recent years, and is transforming the computational representation of atmospheric processes. Large-scale models have so far been trained on coarse-resolution model data and thereby inherited some weaknesses of classical models in the representation of important but small-scale processes in the atmospheric boundary-layer. To make the next leap forward in deep learning of atmospheric processes, we intend to train a model on high-resolution model output and observations. We thereby aim at improving deep learning models beyond the limitations of current models.
We are looking for a deep learning expert interested in applying his or her knowledge to weather and climate processes, in particular in the atmospheric boundary layer.
The use of deep learning for weather forecasting has exploded in recent years, and is transforming the computational representation of atmospheric processes. Large-scale models have so far been trained on coarse-resolution model data and thereby inherited some weaknesses of classical models in the representation of important but small-scale processes in the atmospheric boundary-layer. To make the next leap forward in deep learning of atmospheric processes, we intend to train a model on high-resolution model output and observations. We thereby aim at improving deep learning models beyond the limitations of current models.
We are looking for a deep learning expert interested in applying his or her knowledge to weather and climate processes, in particular in the atmospheric boundary layer.
Your Tasks
- You will fine-tune a pre-trained foundational model such as Atmorep or Aurora using diverse data from large-eddy simulations, direct numerical simulations and observations of the real atmosphere.
- You will collaborate with atmospheric scientists in our group and machine-learning experts from the Helmholtz AI program to develop a setup that allows to train a generalizable model of atmospheric boundary-layer processes.
- Tasks also include the presentation of results at conferences and publishing results as scientific papers.
Your Profile
Preferred Qualifications and Skills
- PhD with a focus on machine learning
- Experience with deep learning methods, particularly with transformer-based architectures
- Good knowledge of English as a working language
Preferred Qualifications and Skills
- Prior experience in Earth system modelling is a bonus.
Further Information
For any questions you may have, you are very welcome to get in touch with Dr Felix Pithan (felix.pithan@awi.de; +49(471)4831-2601).
This is a full-time position, limited to 3 years. It is also suitable for part-time employment. The salary will be paid in accordance with the Collective Agreement for the Public Service of the Federation (Tarifvertrag des öffentlichen Dienstes, TVöD Bund), up to salary level 13. The place of employment will be Bremerhaven.
Postdocs have to register with AWI's postdoc office PROCEED, thereby gaining access to a set of tailor-made career development tools.
For any questions you may have, you are very welcome to get in touch with Dr Felix Pithan (felix.pithan@awi.de; +49(471)4831-2601).
This is a full-time position, limited to 3 years. It is also suitable for part-time employment. The salary will be paid in accordance with the Collective Agreement for the Public Service of the Federation (Tarifvertrag des öffentlichen Dienstes, TVöD Bund), up to salary level 13. The place of employment will be Bremerhaven.
Postdocs have to register with AWI's postdoc office PROCEED, thereby gaining access to a set of tailor-made career development tools.
The AWI is characterized by
- our scientific success - excellent research
- collaboration and cooperation - intra-institute, national and international, interdisciplinary
- opportunities to develop – on the job and towards other positions
- an international environment – everyday contact with people from all over the world
- flexible working hours and the possibility of mobile working up to 50% of regular working hours
- health promotion and company fitness with Hansefit and Wellhub
- support services and a culture of reconciling work and family
- occupational pension provision (VBL)
AWI values diversity and actively promotes gender parity, as well as an open, inclusive environment that provides equal opportunities. We are convinced that diverse teams and a variety of perspectives enrich our work and our daily collaboration. In a continuous process of learning and reflection, we aim to ensure that all our employees can be themselves and feel a sense of belonging. We welcome applications from qualified people regardless of binary and non-binary genders, race and nationality, ethnic and social background, religion, age, physical abilities, neurodivergence, sexual orientation, and other identities.
Applicants with disabilities will be given preference when equal qualifications are present.
Applicants with disabilities will be given preference when equal qualifications are present.
AWI fosters work-family compatibility in various ways and has received several awards as a result of this commitment. And as a new international member of our team, you can be sure that we will help you settle in. Our Family Office and International Office will be glad to support you, even before you start at AWI.
We look forward to your application!
Please submit your application by September 24th 2024, exclusively online.
Reference number: 24/150/G/Kli-b
Please submit your application by September 24th 2024, exclusively online.
Reference number: 24/150/G/Kli-b