Research scientist (f_m_x) - GNSS Reflectometry

Gfz Potsdam; Potsdam; Vor Ort; EUR 38.000 - 56.000; Vollzeit

Benefits dieser Stelle

Public service benefits

Extensive training opportunities

Career development support

Zusammenfassung

GFZ Potsdam in Potsdam, Germany, invites applications for a Research Scientist (f_m_x) in GNSS Reflectometry. The role focuses on developing AI/ML methods for land GNSS reflectometry, soil moisture retrieval, and related land-surface variables, in an international setting.

The successful candidate will join the GNSS remote sensing team for a fixed-term of one year, with a start date of 1 November 2026, salary group 13 (TVöD Bund), and part-time 75% (29.25 h/week) working hours at Potsdam.

Qualifikationen

• Master's degree (or equivalent) and a PhD in geodesy, remote sensing, geophysics, physics, environmental or data science, ideally with a focus on GNSS reflectometry.
• Publications on GNSS reflectometry or related microwave remote sensing techniques.
• Knowledge of machine learning methods for processing remote sensing data.
• Experience in GNSS data processing from ground- and satellite-based sources.
• Excellent command of English (working language).

Aufgaben

• Develop GNSS reflectometry-based remote sensing methods for land-surface applications, including soil moisture and vegetation/snow/freeze–thaw analysis.
• Validate GNSS reflectometry data products against satellite/radar and in-situ data to improve quality and error characterization.
• Apply advanced machine learning to GNSS reflectometry data to enhance meteorological and hydrological models and forecasts.
• Collaborate with international partners and contribute to publications and conferences.

Kenntnisse

Master's degree

PhD

GNSS reflectometry

Machine learning

English proficiency

Ausbildung

Master's degree in geodesy/remote sensing/geophysics/physics/environmental or data science

PhD in geodesy/remote sensing/geophysics/physics/environmental or data science

Tools

Python

MATLAB

UNIX/Linux

Deep-learning frameworks

Jobbeschreibung

The GFZ Helmholtz Centre for Geosciences is one of the world's leading institutions in the field of geosciences. As part of the Helmholtz Association, Germany's largest research organisation, we address global challenges such as natural hazards, climate change and the sustainable use of resources. In doing so, we combine cutting-edge research with social relevance. Our international staff - around 1,200 employees and approx. 500 guests - work in a multidisciplinary way and with a unique infrastructure to research the dynamic processes of the Earth system. Our vision: “Taking the pulse of the Earth to safeguard a habitable planet.”

For section 1.1 Space Geodetic Techniques (department “Geodesy”), we are looking for a:

Research scientist (f_m_x) - GNSS Reflectometry

Reference Number 11507

Our section develops and applies GNSS-based Earth observation techniques, including GNSS reflectometry (GNSS-R) and atmosphere/ionosphere sounding. GNSS reflectometry methods rely on the use of GNSS signals for remote sensing of the Earth’s surface, using both ground- and satellite-based techniques. Data from regional and global ground networks, specialised flight experiments, and low-Earth-orbit satellite missions (e.g., CYGNSS, HydroGNSS) are processed and widely used in Earth System science.

The advertised position focuses on developing and applying artificial intelligence (AI) and machine learning methods for GNSS reflectometry over land, particularly for the retrieval and analysis of soil moisture and related land-surface variables. It combines current and innovative research tasks with operational aspects in an international environment involving interdisciplinary partner institutions. The successful candidate will join the GNSS remote sensing team of section 1.1 for a fixed term of one year.

Your responsibilities:

• Further development of GNSS reflectometry-based remote sensing methods for land-surface applications, particularly for determining soil moisture, as well as for analysing vegetation and snow/freeze–thaw properties under operational conditions, using signals from all GNSS systems (GPS, Galileo, GLONASS, and BeiDou)
• Validation of GNSS-based reflectometry data products through comparison with other remote sensing data (e.g., satellite radar and radiometer observations) as well as in-situ measurements, to improve data quality, quality assurance, and error characterisation
• Development and application of advanced machine learning methods for data analysis and exploiting innovative GNSS reflectometry products to improve meteorological and hydrological models and forecasts
• Active collaboration with international and interdisciplinary partner institutions, and contribution to peer-reviewed publications and conference presentations

About You:

Essential Qualifications:

• A Master's degree (or equivalent) and a PhD in geodesy, remote sensing, geophysics, physics, environmental or data science, or a closely related field, ideally with a focus on GNSS reflectometry
• Proven experience and scientific publications on the development and geophysical application of GNSS reflectometry or related microwave remote sensing techniques
• Sound knowledge of machine learning methods for processing and analysing remote sensing data
• Experience in GNSS data processing and the handling of ground- and satellite-based GNSS remote sensing data
• Very good command of English (working language)

Desirable Qualifications:

• Experience
  • with spaceborne GNSS-R missions and their data products (e.g., CYGNSS, HydroGNSS)
  • in developing scientific software, e.g., in Python and/or MATLAB, as well as in-depth knowledge of UNIX/Linux environments; familiarity with modern deep-learning frameworks
  • with high-performance computing and the handling of large, heterogeneous satellite datasets

What we offer:

• Ambitious and varied tasks in a dynamic and international research environment
• State-of-the-art equipment
• Public service benefits
• Extensive training opportunities
• Professional career advice offered by our in-house Career-Centre
• Flexible working hours and conditions
• Support with finding a good work-life balance offered by benefit@work
• Institute day-care centre on site
• Working at the Albert Einstein Science Park on the Telegrafenberg in Potsdam
• Workplace within walking distance of Potsdam main train station, or just a short ride on the shuttle bus

Start date: 1st November 2026
Fixed-term: 12 months
Salary: The position is classed as salary group 13 according to “TVöD Bund ”. The salary group is determined on the basis of the Collective Wage Agreement and the respective personal qualifications.
Working hours: Part-time 75% (currently 29.25 h/week)
Place of work: Potsdam

Important Technical Note: Currently, email addresses associated with domains such as @hotmail.com, @outlook.com, or @live.de may experience occasional delays or restrictions in receiving messages. To ensure smooth communication during the application process, we recommend using an alternative email address and providing an additional contact method (e.g., a phone number).

The GFZ actively promote diversity and equal opportunities. We explicitly welcome applications from all qualified individuals, regardless of ethnic and social origin, nationality, gender, sexual orientation and identity, religion/belief, age, and physical or neurodiverse abilities.

“Diversity in perspectives” is one of GFZ's core values. As an integral part of supporting diversity at our centre, we actively promote women in science and in leadership positions. To know more about our Diversity policies, contact the diversity team. If you need more information about our gender equality policies, please do not hesitate to contact our Equal Opportunities Officer and check our Equal Opportunities Plan & Cascade Model.

We look forward to applications from people who enjoy working in diverse teams, where everyone feels respected and valued and can fully develop their own talents. Applicants with severe disabilities and equalised persons will receive preferential consideration if equally qualified.

Data protection information for applicants

In case of any further queries regarding the field of activity, please contact Prof. Dr. Jens Wickert either via email or by phone at [phone]. If you have any general questions about the application process, please contact our recruiting team at our phone number [phone].