Postdoctoral Research Associate - Empirical process inference for coupled ocean-atmosphere variability and extreme events
Magdeburg-Stendal University of Applied Sciences (h2.de)
H2 is a medium-size university of applied sciences with about 5,800 students and more than 500 employees located in the heart of Germany’s federative state of Saxony-Anhalt. With its two university campuses in Magdeburg and Stendal, it is based in two long recognized centers of creativity and offers ideal study, working and living conditions. An interdisciplinary environment of engineering, economics, health sciences and humanities provides modern and innovative study programs and superior teaching and research standards.
H2 seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourage women to apply. Efforts to combine job and family are supported in various ways. Applications of disabled persons with equal qualifications will be regarded favorably.
Climate: Past, Present & Future (CL)
Nonlinear Processes in Geosciences (NP)
Magdeburg-Stendal University of Applied Sciences (H2) – in partnership with the Potsdam Institute for Climate Impact Research (PIK) – seeks to fill one position as a postdoctoral scientist starting as soon as possible. The position is part of the new multilateral project ROADMAP – The Role of ocean dynamics and Ocean-Atmosphere interactions in Driving cliMAte variations and future Projections of impact-relevant extreme events, which has recently been approved by the Joint Program Initiatives JPI Climate and JPI Oceans.
ROADMAP represents an ambitious research program to gain robust, relevant and transferable knowledge of past, present and future spatiotemporal patterns of climate variability and extremes and the underlying role of ocean dynamics and ocean-atmosphere interactions. The main focus of the planned studies will be on the effects of North Atlantic and North Pacific sea surface variability on extratropical atmospheric circulation, especially on the emergence of large-scale weather patterns associated with high-impact extreme events. ROADMAP will systematically evaluate big climate datasets from observations and large-scale climate model ensembles originating from both existing coordinated international programs and targeted experiments performed within the project. Members of the ROADMAP consortium include several leading research institutions from Germany, France, Norway, Italy, Belgium, Portugal and Ireland coordinated by the Max Planck Institute for Meteorology in Hamburg.
The postdoctoral scientist based at H2 will be responsible for the identification, development and implementation, and application of complex systems and data science methods with particular emphasis on causal interrelationships, scale-dependent processes and interactions between processes with different intrinsic time-scales. These tasks require a close collaboration with the different ROADMAP partners, which will in turn identify special requirements for methodological improvements according to specific climate subsystems to be studied and provide large-scale data sets from various state-of-the-art global climate models.
The position will be associated with the Professorship for Data Science and Stochastic Modeling (Prof. Reik Donner) at the Department for Water, Environment, Construction and Safety at H2. The successful candidate will perform most of the research work as a guest scientist based at PIK’s Research Department 1 (Earth System Analysis) closely collaborating with the Research Department 4 (Complexity Science) and is expected to actively contribute to the overarching scientific activities of the involved research groups. The willingness to co-supervise student assistants as well as research students within the designated topical field is expected.
Qualification: The successful applicant should hold a PhD degree (or equivalent) in physics, mathematics/statistics, climate science or some other topically relevant discipline, or expect to obtain this degree within a short period of time. The complex tasks of the project require a solid background in applied mathematics/statistics, ideally supported by advanced knowledge of nonlinear dynamics and time series analysis. Prior experience in working with large climate datasets would be most welcome. We additionally expect advanced scientific programming skills (preferably in Python/Matlab/R) and a willingness to integrate into an interdisciplinary team and collaborate with the national and international project partners, including short-term research exchanges and participation in national and international scientific conferences.
Interested candidates should send their complete application (in English or German language) exclusively by email (a single PDF file, 5 MB max.), including at least a detailed C.V., a short letter of motivation and either (i) one or more recommendation letters or (ii) corresponding contact details from former supervisors or close collaborations, to email@example.com
Magdeburg-Stendal University of Applied Sciences
Human Resources Department
with a copy to Prof. Reik Donner, email: firstname.lastname@example.org, who will also be happy to answer any individual questions regarding this vacancy. When submitting your application, please quote the reference number 63/2020 in the subject line of your message.
Review of incoming applications will start after June 8th, 2020 and continue until the position is filled.