PhD Positions: AI for Weather and Climate
Join an interdisciplinary doctoral project combining machine learning and Earth science at TU Delft and BFH.
Best for:Best for master's graduates in physics, computer science, or related quantitative fields with strong Python skills and an interest in climate science or machine learning.
Overview
The Energy Weather & AI Lab at TU Delft and Bern University of Applied Sciences (BFH) invites applications for multiple 4-year PhD positions focused on applying artificial intelligence to weather forecasting, climate science, and energy applications. Researchers will investigate machine learning, remote sensing, physics-based modeling, and generative models to address pressing climate and energy transition challenges. Successful candidates will be embedded in the Department of Geoscience and Remote Sensing at TU Delft, where they will ultimately receive their doctoral degrees. The fully funded positions offer competitive salaries, conference travel support, and opportunities to engage in teaching and student supervision.
What you'll do
- Conduct cutting-edge scientific research on topics related to AI for weather and climate applications
- Publish research findings in peer-reviewed international journals and present them at academic conferences
- Collaborate actively with project stakeholders and international research partners
- Organize project activities, attend regular team meetings, and discuss research progress and results
- Assist in teaching duties and co-supervise undergraduate students
Requirements
Degree required: MSc degree or equivalent in physics, machine learning, computer science, atmospheric or geoscience, engineering, applied mathematics, or a related field
Degree offered: PhD
Language: English; strong written and verbal communication skills
Instruction: English
- Strong programming skills including proficiency in Python
- Solid foundation in machine learning, statistics, computer vision, image processing, or signal analysis
- Excellent analytical, quantitative, and scientific modeling skills
- Ability to work independently as well as collaboratively in an international team
- Self-motivated and proactive approach to tackling complex scientific challenges
- Applicants must hold a relevant Master of Science degree or equivalent by the start date
Funding & terms
How to apply
Deadline: Open until the position is filled · open until filled
Interested candidates should submit their application materials through the designated portal or application channel provided by the hiring institutions. Ensure all requested documents, including academic transcripts and CV, are included in the submission package.
- CV
- Academic transcripts
- Cover letter
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