PhD Position (f_m_x) “Causal and mechanism discovery for multi-scale and spatiotemporal data"
PhD Position (f_m_x) “Causal and mechanism discovery for multi-scale and spatiotemporal data"

PhD Position (f_m_x) “Causal and mechanism discovery for multi-scale and spatiotemporal data"

Potsdam Doktorand 45000 - 60000 € / Jahr (geschätzt) Kein Home Office möglich
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Auf einen Blick

  • Aufgaben: Dive into causal discovery and machine learning for geoscience data analysis.
  • Arbeitgeber: Join the Helmholtz Centre Potsdam, a leader in geoscience research.
  • Mitarbeitervorteile: Enjoy flexible hours, extensive training, and public service benefits.
  • Warum dieser Job: Make an impact on climate research while collaborating with top experts.
  • Gewünschte Qualifikationen: Master's in relevant fields and programming skills in Python or C required.
  • Andere Informationen: Position starts January 2025; apply by October 31, 2024.

Das voraussichtliche Gehalt liegt zwischen 45000 - 60000 € pro Jahr.

The Helmholtz Centre Potsdam – GFZ German Research Centre for Geosciences is the national centre for research into the geosphere. With around 1,650 employees, we develop a sound understanding of systems and processes of the solid Earth as well as strategies and options for action to counter global change, understand natural hazards and sustainably secure energy and raw material requirements.

In Section 4.7 “Earth Surface Process Modelling” (Department 4 “Geosystems”), we are looking for a student for:

PhD Position (f_m_x) “Causal and mechanism discovery for multi-scale and spatiotemporal data in geoscience”

Reference Number 9808

Time series, such as seismic data or paleoclimate proxy data (such as stable isotopes) from lake deposits, are one of the most common data structures in geoscience. Detecting causal associations and understanding mechanisms based on them is a key challenge for providing insights and predicting behaviors in Earth system. We seek a candidate to develop (1) a causal and equation discovery framework for various time series and spatiotemporal datasets; and (2) a statistical learning model for detecting and predicting phase transition and tipping points in Earth system components and critical thresholds for hazard early warning system. This project will mainly use seismic data for hazard early warning of mass movement events and isotope time series for paleoclimate reconstruction from various sites in Europe and worldwide for identifying regime transitions.

The PhD position will be hosted in the Earth Surface Process Modelling section at the GFZ and supervised by Dr. Hui Tang. In the section, numerical models are developed and used to investigate a wide range of physical, chemical and biological processes and interactions occurring at the Earth’s surface that are driven by tectonic processes and modulated by climate. The successful candidate will work with a team of partners from the Geomorphology section at the GFZ (Prof. Dr. Dirk Sachse) and from the Complex Systems department at the Potsdam Institute for Climate Impact Research (PD Dr. Norbert Marwan).

Your responsibilities:

  1. Process and analyse continuous time series data such as seismic data and isotope data
  2. Develop and improve causal discovery framework for continuous time series
  3. Develop and improve equation discovery framework (e.g., SINDy) for continuous time series
  4. Develop a machine learning approach for determining tipping points in Earth system and critical thresholds for early warning system based on causal and equation discovery framework, especially for mass movement
  5. Build a statistical framework for ensemble simulations deriving thresholds for future climate
  6. Interact with other members of the Earth Surface Process Modeling Section at weekly group meetings and in other informal ways
  7. Present results at scientific meetings and in publications in peer-reviewed journals
  8. Supervise master’s students

Your qualifications:

  1. Master degree or diploma in Mathematics, Data Science, Machine Learning or Geosciences
  2. Programming skills in Python, C, or similar language are necessary
  3. Familiarity with machine learning and data science is strongly desirable
  4. Knowledge in seismology or geochemistry is desirable
  5. Proficiency in spoken and written English

What we offer:

  1. Ambitious and varied tasks in a dynamic and international research environment
  2. State-of-the-art equipment
  3. Public service benefits
  4. Extensive training opportunities
  5. Professional career advice offered by our in-house Career-Centre
  6. Flexible working hours and conditions
  7. Support with finding a good work-life balance offered by
  8. Institute day-care centre on site
  9. Working at the Albert Einstein science park on the Telegrafenberg in Potsdam
  10. Work place within walking distance of Potsdam main train station, or just a short ride on the shuttle bus

Start date: 1st January 2025
Fixed-term: 36 months
Salary: The position is classed as salary group 13 according to “TVöD Bund (Tarifgebiet Ost)”. 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

Have we piqued your interest?
If so, we look forward to receiving your application by 31st October 2024. Please use our online application form only.

Diversity and equal opportunities are integral components of our human resources policy. The GFZ actively promotes diversity and explicitly welcomes applications from all qualified individuals, regardless of ethnic and social origin, nationality, gender, sexual orientation and identity, religion/belief, age and physical characteristics. Anyone who has been recognised as severely disabled, will be given preferential consideration in the event of equal suitability and qualification in accordance with the provisions of the German Social Code IX.

Your personal data will be processed for the purpose of conducting the selection procedure on the basis of Art. 6 para. 1 b, Art. 88 GDPR in conjunction with Art. 26 of the Data Protection Act for the State of Brandenburg. After completion of the procedure, application documents will be deleted in compliance with data protection regulations.

In case of any further queries relating to the field of activity, please contact Dr. Hui Tang (). If you have any general questions about the application process, please contact our recruiting team at our phone number +49 (0) 331-6264-28787.

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PhD Position (f_m_x) “Causal and mechanism discovery for multi-scale and spatiotemporal data" Arbeitgeber: Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum GFZ

The Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences is an exceptional employer, offering a dynamic and international research environment that fosters innovation and collaboration. With extensive training opportunities, professional career advice, and a strong commitment to work-life balance, employees can thrive both personally and professionally. Located in the scenic Albert Einstein science park in Potsdam, the centre provides state-of-the-art facilities and a supportive community, making it an ideal place for aspiring researchers to advance their careers in geoscience.
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Kontaktperson:

Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum GFZ HR Team

StudySmarter Bewerbungstipps 🤫

So bekommst du den Job: PhD Position (f_m_x) “Causal and mechanism discovery for multi-scale and spatiotemporal data"

Tip Number 1

Make sure to familiarize yourself with the latest research in causal discovery and machine learning, especially as it pertains to geosciences. This will not only help you understand the current challenges but also allow you to discuss relevant topics during your interviews.

Tip Number 2

Engage with the scientific community by attending conferences or workshops related to geosciences and data science. Networking with professionals in the field can provide valuable insights and potentially lead to recommendations for your application.

Tip Number 3

Consider reaching out to current or former PhD students at GFZ to gain insights into their experiences. They can offer tips on what the selection committee values and how to best present your skills and interests.

Tip Number 4

Stay updated on advancements in seismic data analysis and paleoclimate reconstruction. Being knowledgeable about recent developments will demonstrate your passion for the field and your readiness to contribute to the team.

Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: PhD Position (f_m_x) “Causal and mechanism discovery for multi-scale and spatiotemporal data"

Master degree or diploma in Mathematics, Data Science, Machine Learning or Geosciences
Programming skills in Python, C, or similar language
Familiarity with machine learning and data science
Knowledge in seismology or geochemistry
Statistical analysis
Causal discovery framework development
Equation discovery framework development (e.g., SINDy)
Machine learning for tipping points detection
Ensemble simulations for climate thresholds
Data processing and analysis of time series data
Strong communication skills in spoken and written English
Ability to work collaboratively in a research team
Presentation skills for scientific meetings and publications

Tipps für deine Bewerbung 🫡

Understand the Project: Make sure to thoroughly read the job description and understand the specific requirements of the PhD position. Familiarize yourself with the concepts of causal discovery, time series analysis, and machine learning as they relate to geosciences.

Tailor Your CV: Highlight your relevant academic background, particularly in Mathematics, Data Science, Machine Learning, or Geosciences. Include any programming skills in Python or C, and mention any experience with seismic data or machine learning projects.

Craft a Strong Motivation Letter: In your motivation letter, express your passion for geosciences and research. Discuss why you are interested in this specific project and how your skills align with the responsibilities outlined in the job description.

Prepare for Potential Interviews: While this step comes after application submission, it's good to prepare in advance. Be ready to discuss your previous work, your understanding of the research area, and how you can contribute to the team at GFZ.

Wie du dich auf ein Vorstellungsgespräch bei Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum GFZ vorbereitest

Understand the Research Focus

Make sure to familiarize yourself with the specific research areas of the Earth Surface Process Modelling section. Being able to discuss how your background in Mathematics, Data Science, or Geosciences aligns with their work will show your genuine interest and preparedness.

Showcase Your Technical Skills

Prepare to discuss your programming skills in Python, C, or similar languages. Be ready to provide examples of projects where you applied machine learning techniques or worked with time series data, as this is crucial for the role.

Discuss Collaboration Experience

Highlight any previous experiences working in teams or collaborating on research projects. The position involves interaction with various partners, so demonstrating your ability to work well in a team setting will be beneficial.

Prepare Questions About the Role

Think of insightful questions regarding the PhD project, such as the methodologies used for causal discovery or the types of datasets you will be working with. This shows your enthusiasm and critical thinking about the position.

PhD Position (f_m_x) “Causal and mechanism discovery for multi-scale and spatiotemporal data"
Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum GFZ
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