Postdoc on spatially compounding events (f/m/x)

Place of work

Working time

The job position is available for full-time or part-time employment.

Contract limitations

Salary

Contact

Your contact for any questions you may have about the job:
jakob.zscheischler@ufz.de

Your application

Please submit your application via our online portal with your cover letter, CV (please omit your photo, age, or marital status) and relevant attachments.

Diversity and Inclusion

The UFZ has a strong commitment to diversity and actively supports equal opportunities for all employees regardless of their origin, religion, ideology, disability, age or sexual identity.
We look forward to applications from people who are open-minded and enjoy working in diverse teams.

Your tasks

• Develop and apply statistical or machine learning tools to study spatially compounding events such as concurrent floods, drought, or heatwaves and their impacts
• Explore worst case events in the present and future
• Publish results in scientific journals

We offer

• The freedom to master even the most demanding challenges between basic research and practical application
• The chance to work in interdisciplinary, international teams and benefit from a variety of perspectives
• Firstclass integration into national and international research networks to work together on global challenges
• Excellent research infrastructure and research data management to optimally support your work
• Flexible working hours and a wide range of options for balancing work and care responsibilities through our family office
• Competent support and advice for international colleagues arriving at the UFZ from the 'International Office'
• Special annual payment, capital-forming benefits and subsidised Germany Job Ticket
• A workplace in a vibrant region with a high life quality and social and cultural diversity

Your profile

• PhD in climate or science, environmental sciences, statistics, physics or related field
• Excellent data handling and programming skills
• Background in compound event research
• Experience with multivariate statistics/extreme value theory and/or machine learning
• Open minded, pro-active, independent researcher
• Excellent writing skills