Global land ecosystem modelling at IMK-IFU

Open Positions

Karlsruhe Institute of Technology (KIT) is the result of the merger of former Karlsruhe University and Research Center Karlsruhe. It is a unique institution in Germany, which combines the mission of a university with that of a large-scale research center of the Helmholtz Association. With 9400 employees and an annual budget of EUR 800 M., KIT is one of the largest research and education institutions worldwide.

Scientific Programmer (f/d/m):
Modelling terrestrial ecosystems response to environmental changes

We seek a creative and communicative colleague to join the land-ecosystem modelling group (LEMG; https://lemg.imk-ifu.kit.edu/) in our Institute of Meteorology and Climate Research - Atmospheric

Environmental Research (IMK-IFU) in Garmisch-Partenkirchen. You will be developing highly advanced model systems (dynamic global vegetation models, functional biodiversity models, coupled socioeconomic/ ecological models). Your skills will help to solve questions of utmost importance, posed by the combined challenges of climate change, land-use change and biodiversity loss.

Tasks include:

  • Contribute to various development tasks, code development and documentation of the models LPJGUESS, Madingley and LandSyMM (more information available at the LEMG website)
  • Contribute to simulations and analyses of model output
  • Support other members of the team in code development and simulation set-up
  • Contribute to publications arising from the work
  • Contribute to general tasks in the team such as teaching, ordering of computing equipment, project
  • reports or proposal writing

We are: a multi-disciplinary, collaborative and friendly team, well connected to national and international research networks and activities. This includes close cooperation with colleagues at IMK-FU, Lund University (Sweden), Edinburgh (UK), Western Sydney (AU) and many others worldwide.

The foreseen starting date is flexible, ideally late 2023/early 2024. The appointment will be initially for a period of two years; extension up to five years is possible, depending on previous years of work in the German public sector, on successfully achieving set milestones in the foreseen tasks, and continued availability of funds. Salary and benefits will be based on the Collective Agreement for the German Public Service Sector (TV-L).

Required qualifications:

  • MSc or PhD in a relevant subject (e.g., environmental science, meteorology, information technology,
  • atmospheric physics, ecology)
  • In-depth, practical knowledge of modern coding and data-analyses languages (e.g., C++, R, Python...;
  • GIS is insufficient)
  • Proven track-record in advanced scientific programming or quantitative data-analysis
  • You will need to be willing to travel and have very good spoken and written skills in the English language

 

Candidates will be evaluated based on their track record, adjusted for their seniority, parental leave, etc. We highly value diversity in our team, and encourage in particularly female or diverse candidates to apply. Applications, including a letter of motivation, your CV including a short description of your previous programming experience, and contact details of two referees should be sent by email as a single pdf to Prof. Almut Arneth (almut.arneth(at)kit.edu) by 24.08.2023, quoting the reference number LEMG-SP.

You will be notified about the outcome of an initial screening of applications by early September, but we do not have the capacity to respond to incomplete applications and those that do not fit the required profile. The position will remain open until filled.

 

 

Researcher (f/d/m):
Modelling terrestrial ecosystems response to environmental changes

We seek a creative and communicative colleague to join the land-ecosystem modelling group (LEMG; https://lemg.imk-ifu.kit.edu/) in our Institute of Meteorology and Climate Research - Atmospheric Environmental Research (IMK-IFU) in Garmisch-Partenkirchen. You will be applying advanced model systems (especially the dynamic global vegetation model LPJ-GUESS; working with functional biodiversity models (e.g. Madingley), coupled socioeconomic/ecological models (e.g. LandSyMM) will also be possible; see information and links under 'Themes'). Your skills will help to solve questions of utmost importance, posed by the combined challenges of climate change, land-use change and biodiversity loss.

Tasks include:

We are: a multi-disciplinary, collaborative and friendly team, well connected to national and international research networks and activities. This includes close cooperation with colleagues at IMK-IFU, Lund University (Sweden), Edinburgh (UK), Western Sydney (AU) and many others worldwide. You will have the opportunity to further enhance your academic career through leading tasks and cooperating in the ongoing projects, and by developing project proposals, jointly with the head of the group.

The foreseen starting date is flexible, ideally late 2023/early 2024. The appointment will be initially for a period of two years; extension up to five years is possible, depending on previous years of work in the German public sector, on successfully achieving set milestones in the foreseen tasks, and continued availability of funds. Salary and benefits will be based on the Collective Agreement for the German Public Service Sector (TV-L).

Required qualifications:

  • PhD in a relevant subject (e.g., environmental science, meteorology, information technology,
  • atmospheric physics, ecology)
  • Practical knowledge of modern coding and data-analyses languages (e.g., C++, R, Python...)
  • Proven track-record in running simulations and quantitative data-analysis (GIS is insufficient)
  • Above-average publication record and having applied successfully for funding previously is an
  • advantage
  • You will need to be willing to travel and have very good spoken and written skills in the English language Candidates will be evaluated based on their track record, adjusted for their seniority, parental leave, etc.

We highly value diversity in our team, and encourage in particularly female or diverse candidates to apply.

Applications, including a letter of motivation, your CV including a short description of your previous research and programming experience, and contact details of two referees, should be sent by email as a single pdf to Prof. Almut Arneth (almut.arneth(at)kit.edu) by 24.08.2023, quoting the reference number LEMG-PD. You will be notified about the outcome of an initial screening of applications by early September, but we do not have the capacity to respond to incomplete applications and those that do not fit the required profile. The position will remain open until filled.

HiWi, Bachelor and Master thesis opportunities

Hilft uns eine erhöhte CO2-Konzentration bei der Ernährung der Welt?

We have regularly opportunities for HiWi jobs, and topics suitable for Bachelor and Master theses, please contact us if you are interested. For most of these you will need to have some experience in handling large data sets (e.g. R, MatLab, Python), ideally even in programming languages, and an interest in our topics.

Small student-contracts to cover living costs in Garmisch can be offered.

In particulare we seek interested students to work on theses on two topics (description in German as follows):

  1. Hilft eine erhöhte CO2-Konzentration bei der Ernährung der Welt? Eine wachsende Weltbevölkerung in Verbindung mit den Auswirkungen des Klimawandels wird das globale Ernährungssystem in den kommenden Jahrzehnten voraussichtlich extrem belasten. Eine 'gute' Nachricht, inmitten der schlechten ist, dass erhöhte atmosphärische Kohlendioxidkonzentration in Feldexperimenten nachweislich zu einer erheblichen Steigerung der Ernteerträge führt. Eine große Herausforderung für die Wissenschaft besteht darin, diese Informationen aus Experimenten in Simulationen und Projektionen von Ertragsveränderungen in ganzen Regionen oder auf der ganzen Welt umzusetzen. In den letzten Jahren haben wir ein Modul für das dynamische globale Vegetationsmodell LPJ-GUESS entwickelt, das genau diese Skalierung ermöglicht. Um besser zu verstehen, ob die simulierten Prognosen realistisch sind, ist eine sorgfältige Bewertung des Modells anhand von Beobachtungen erforderlich.
    In diesem Masterprojekt werden Sie mit der neuesten Version des LPJ-GUESS-Erntemodells arbeiten,
    Simulationen historischer und potenzieller künftiger Ernteerträge durchführen, diese anhand von Beobachtungen bewerten und die Gründe für die simulierten starken Ertragssteigerungen untersuchen. Sie erhalten eine Ausbildung in der Anwendung eines hochmodernen wissenschaftlichen Modells und in der Datenverarbeitung. Dabei werden Sie auch etwas über die Prozesse lernen, die bestimmen, wie sich die Ernteerträge in Zukunft wahrscheinlich verändern werden. Ihre Forschung wird zur Verbesserung des LPJ-GUESS-Erntemodells beitragen, das seinerseits eine internationale Zusammenarbeit zwischen Institutionen in Schweden und Deutschland darstellt und zu einer Reihe von internationalen Bewertungen des zukünftigen Ernährungssystems beiträgt (z. B. Alexander et al., 2018 https://onlinelibrary.wiley.com/doi/10.1111/gcb.14110; Rabin et al., 2020 https://esd.copernicus.org/articles/11/357/2020/.
     
  2. Wieviel kosten Feuer?
    Das Risiko von Waldbränden steigt mit dem Klimawandel weltweit an. Eine der Konsequenzen sind erhöhte Brandschäden, aber auch erhöhte Kosten für Feuermanagement. Wie hoch diese sind ist aber nur mir großen Unsicherheiten abzuschätzen. Diese Masterarbeit basiert z.T. auf systematischer Literatursuche und -synthese zu ökonomischen und nicht-ökonomischen Schäden, Statistik & GIS-basierter Analyse, sowie Output zu Waldbränden des Vegetationsmodels LPJ-GUESS (e.g. Rabin, S.S., et al. (2017) The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols with detailed model descriptions. Geoscientific Model Development 10: 1175-1197).
    Ihre Forschung wird zu einer Verbesserung der Brandfolgekosten beitragen. Sie erhalten Einblick in globale Ökosystemmodellierung und deren Auswertung. Die Arbeit erfolgt in Kooperation mit Arbeitsgruppen in München, Frankfurt und Dresden.


Für beide Arbeiten gilt:
Fortgeschrittene Programmierkenntnisse sind keine Voraussetzung, da die LPJ-GUESS-Modellierung ohne
Änderung des zugrundeliegenden C++-Codes durchgeführt werden kann (es sind nur einige grundlegende Befehle in Linux erforderlich), aber die Fähigkeit, Datensätze mit einer programmierbasierten Software wie Matlab oder R zu analysieren, ist für das Projekt von grundlegender Bedeutung, ebenso wie ein Verständnis der Konzepte der Ökosystemmodellierung. Für Thema (2) sind Kenntnisse in GIS-Software nötig.
Die Arbeiten können in deutscher oder englischer Sprache verfasst werden, für die Interaktion mit Kollegen in
sind jedoch gute Englisch’sprech‘kenntnisse erforderlich.