PhD Position – Scalable AI and Advanced Computing for Earth Observation
The Jülich Supercomputing Centre (JSC) operates one of the most powerful computer systems for scientific and technical applications in Europe and makes it available to scientists at Forschungszentrum Jülich, in Germany and across Europe for research purposes via an independent peer-review process. As part of this remit, the JSC carries out research and development work in the fields of technology, HPC systems, communications, highly scalable data science, mathematics and application support. The Large Scale Data Science department develops machine learning techniques and other methods and tools for the management, analysis and modelling of large-scale data, and for the integration of data and computing resources into federated HPC infrastructures. The models, tools and methods are developed in collaboration with users in selected scientific domains, tested, scaled for the pre-zettascale era and offered as generic solutions to a large number of scientific communities. Join us now and contribute with your expertise to this interesting field.
Your Job
In this position, you will join our Simulation and Data Lab for AI and Machine Learning for Remote Sensing. The lab advances interdisciplinary research and operational services by combining geoscience and remote sensing methods with AI and advanced computing technologies for Earth observation (EO) applications, including climate science, forestry, or agriculture. Your doctoral research will investigate how AI methods and workflows can be designed and adapted to handle large, heterogeneous EO tasks efficiently and reliably. You will develop and evaluate approaches that address the trade-offs between predictive performance, computational efficiency and scalability, using high-performance and cloud computing environments. Depending on the agreed research direction, you may also explore hybrid quantum-classical approaches. You will work closely with our researchers and international partners from academia, industry and public agencies.
Specifically, you will:
- Review the scientific literature and formulate research questions at the intersection of AI, EO and advanced computing
- Develop and investigate AI methods for multisource EO data, exploring approaches such as geospatial foundation models and representation learning
- Design reproducible data and experimental workflows for model training, adaptation and evaluation on selected EO applications
- Investigate MLOps pipelines for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems
- Benchmark the developed approaches against established methods, assessing predictive performance, generalisation, computational requirements and scalability
- Collaborate with domain researchers and computing specialists to validate your methods on relevant EO problems and integrate research prototypes into shared software and workflows
- Publish your findings in scientific journals and present them at international conferences, contribute to open-source research software and prepare your doctoral thesis
Your Profile
Your qualifications and technical background include:
- An excellent master’s degree or equivalent in computer science, data science, applied mathematics, physics, scientific computing, remote sensing, geoinformatics or a related field
- A solid foundation in machine learning and relevant mathematical methods, including linear algebra, probability and optimisation
- Experience in one or more of the following areas would be advantageous: EO or geospatial data analysis, parallel or distributed computing, GPU programming, Linux and containerised environments, quantum computing, or agentic AI
- Prior industry experience, publications and open-source contributions are welcome
- Good programming skills, preferably in Python, and practical experience implementing and evaluating machine learning methods through coursework, a thesis, research projects or professional work
- Familiarity with at least one deep learning framework, such as PyTorch or TensorFlow, and an interest in reproducible scientific software development
- Strong motivation to pursue doctoral research at the intersection of AI, EO and advanced computing, with curiosity and a willingness to acquire new methodological and domain knowledge
- An analytical and independent approach to solving problems, together with the ability to collaborate effectively in multidisciplinary and international teams
- Very good command of written and spoken English with extensive vocabulary is required (at least B2 level according to the CEFR), ideally supported by a certificate confirming the language level
Our Benefits for You
- Team & Environment: You will work in a motivated team with an international and interdisciplinary focus – at one of the largest research institutions in Europe
- Doctoral Program: You will be enrolled in the PhD programme in Electrical and Computer Engineering at the University of Iceland. A short research stay in Reykjavík, Iceland, will be planned each year.
- Research & Infrastructure: You will have access to excellent scientific and technical facilities for your work
- Networking & Exchange: You will participate in (international) conferences and project meetings and actively build your scientific network
- Supervision & Support: We will accompany your doctoral studies with continuous, expert guidance from your academic supervisor
- Work-life balance: We offer flexible working hours to help you balance your professional and personal life. You also have the option of flexible working (in terms of location), which is generally possible after consultation and in line with upcoming tasks and (on-site) appointments
- Annual Leave: You get 30 days of annual leave
- Knowledge & Development: Your professional development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS)
- Campus experience: Our research campus in the countryside creates ideal conditions for collegial exchange and sporting activities right on site. Our cafeteria offers a wide range of options—you can enjoy a relaxing lunch break with a lake view
- Fair remuneration: Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (75%) of the TVöD-Bund. In addition to the basic salary, there is an additional year-end bonus under the collective pay agreement amounting to 75% of a monthly salary, as well as capital-forming benefits. All information about the TVöD-Bund collective agreement can be found on the BMI website (pay scale table on page 74 of the PDF download).
- Fixed-term: The position is limited to 3 years but with the prospect of a limited extension period where needed to complete your PhD
- Support for international employees: Our International Advisory Service makes it easier for international employees to get started
In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits
We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.
The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and on specific support options for women: https://go.fzj.de/womens-job-journey
Index number: 2026D-0759
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