PhD position at UFZ Leipzig on Model-based exploration of leverage points to foster sustainable nitrogen management in German agriculture

PhD position at UFZ Leipzig on Model-based exploration of leverage points to foster sustainable nitrogen management in German agriculture

PhD position at UFZ Leipzig on Model-based exploration of leverage points to foster sustainable nitrogen management in German agriculture

The POLISES group (www.polises.de) at the Helmholtz Centre for Environmental Research UFZ Leipzig, Germany, is offering a three years PhD Position on  “Model-based exploration of leverage points to foster sustainable nitrogen management in German agriculture starting May 1, 2022 on with a methodological focus on social-ecological modelling and agent-based modelling.

The aim of the PhD project is to investigate the effects of policy measures for sustainable nitrogen management of farmers in Germany. This shall be achieved by developing an integrated model complex that makes both the socio-economic and the biophysical sides of the system explicit and thus allows the consideration of various types of policy measures as well as feedbacks within the system.

The deadline for application is March 4, 2022.

Your tasks:
  • Develop an agent-based model that includes farmers’ decisions on nitrogen management under a variety of potential policy measures in a dynamic and spatially explicit manner
  • Couple the agent-based model with a (simplified) biogeophysical model that simulates the effect of farmers’ nitrogen management on environmental nitrate pollution, taking into account biogeophysical and the socio-economic feedbacks
  • Parametrize the coupled model with empirical data obtained from different sources
  • Use the model to explore the effect of different policies to change farmers’ nitrogen management on environmental nitrogen pollution and to derive recommendations for the design of such policy measures
  • Collaborate with researchers from different Thematic Areas at UFZ relevant in the given context and thereby foster cross-sectional research activity at the UFZ
Your profile:
  • An excellent master’s degree in a relevant field of research, including system sciences, mathematics, physics, agricultural economics, geography, sustainability science
  • Expertise in modelling and analyzing complex systems (experience in agent-based modelling is beneficial)
  • Proficiency in computer programming (e.g. NetLogo, C++, Java, Python) and advanced statistical methods
  • Deep interest in investigating farmer behavior and its consequences from an interdisciplinary perspective, involving sociological, economical, ecological and biogeophysical considerations
  • Excellent knowledge of spoken and written English and ambition to publish in international journals
  • High motivation to work in an international and interdisciplinary team
  • Readiness to travel within and beyond Europe to attend conferences, workshops and courses
Two postdoctoral researchers in land-based, climate change mitigation modelling for the European forest sector (Karlsruhe Institute of Technology)

Two postdoctoral researchers in land-based, climate change mitigation modelling for the European forest sector (Karlsruhe Institute of Technology)

Two postdoctoral researchers in land-based, climate change mitigation modelling for the European forest sector (Karlsruhe Institute of Technology)

                                                                  

Overview

We are seeking two postdoctoral researchers in the field of land-based, climate change mitigation modelling for the forest sector in Europe. The positions will contribute to the European Commission funded (Horizon Europe) ForestPaths project, held within the Land Use & Climate Change Research Group (https://landchange.imk-ifu.kit.edu/) and the Global Land Ecosystem Modelling Group (https://lemg.imk-ifu.kit.edu/) of the Karlsruhe Institute of Technology (KIT), located at KIT’s attractive ‘Campus Alpin’ in Garmisch-Partenkirchen, Germany. Specifically, we seek to employ:

  • A land use modeller to further develop, test and apply the CRAFTY agent-based model of land use change (see: https://landchange.imk-ifu.kit.edu/CRAFTY) in evaluating land-based, climate change mitigation scenarios and policy options for the forest sector in Europe. You will contribute to the coupling of CRAFTY with the LPJ-GUESS vegetation model within the LandSyMM modelling framework (https://landsymm.earth/) and use the model to explore policy pathways, including engaging with key policy stakeholders (ref: FP-LUCCG);
  • An ecosystem modeller to further develop, test and apply the LPJ-GUESS vegetation model (https://lemg.imk-ifu.kit.edu/themes/land-climate-interactions) in evaluating vegetation dynamics and carbon cycling for the forest sector in Europe. You will contribute to improving and testing forest management implementation in LPJ-GUESS and explore, for a range of scenarios, how these affect carbon uptake as well as habitat structural diversity (ref: FP-LEMG).

Your specific roles will be to contribute to the further development and application of these models individually, but also in an integrated way within the LandSyMM modelling framework (https://landsymm.earth/). The positions will also entail small contributions to teaching and group administration. We offer a multi‐disciplinary, highly collaborative and friendly team, well connected to national and international research networks and activities. Salary and benefits will be based on the Collective Agreement for the German Public Service Sector (TV‐L EG13). The positions are available from June 2022 for 2 years initially with the potential for extension beyond this period.

Qualifications

You will have a PhD degree in a relevant discipline and strong quantitative skills in computer modelling and coding (e.g., Fortran, C, C++, Java, Python) and the analysis of large-scale datasets in the environmental sciences (GIS experience alone is insufficient). Depending on the position applied for, experience with statistical analysis, scenario analysis, ecological economics, ecosystem modelling, computational social sciences and/or computer programming is desirable. You will need to have proficiency in the English language, both spoken and in writing and preferably a working knowledge of German. Willingness to travel to interact with consortia partners is required. Further information can be obtained from Prof. Mark Rounsevell (mark.rounsevell@kit.edu) for FP-LUCCG and Prof. Almut Arneth (almut.arneth@kit.edu) for FP-LEMG.

Applications

Applications should be sent by email to Sylvia Kratz (sylvia.kratz@kit.edu) by Friday 18 March 2022, quoting the relevant reference, FP-LUCCG or FP-LEMG. Applications should be submitted within a single PDF document that includes your CV, publications list (with citations), a short (1-2 page) letter of motivation and contact details for 2 referees. The motivation letter should clearly state your computer modelling experience and how your research interests relate to the job specifications provided above. Please also indicate where you heard about this job opportunity. Applications that are incomplete or do not address these criteria will not be considered. Interviews will be held remotely on Thursday 31 March or Friday 1 April 2022. KIT strives to achieve gender balance at all levels of employment. We therefore particularly encourage female candidates to apply for this position. With appropriate qualifications, applications from persons with handicaps are treated preferentially.

Postdoctoral Researcher on the Impact of Climate Adaptation on Poverty Traps (University of Amsterdam)

Postdoctoral Researcher on the Impact of Climate Adaptation on Poverty Traps (University of Amsterdam)

Postdoctoral Researcher on the Impact of Climate Adaptation on Poverty Traps (University of Amsterdam)

Working with Debraj Roy and the Netherlands eScience Center, this position focuses on modelling feedbacks between climate change adaptation and poverty traps dynamics using spatial agent-based models. The focus is on cities in the Global South; collaborations with the Red Cross Red Crescent Climate Centre are foreseen.

The project focuses on modelling the feedbacks between climate change adaptation and poverty traps. Specifically, we study the role of adaptation in shaping risk using spatially explicit modelling of the socio-economic dynamics related to climate change adaptation (CCA), and how dynamics in poverty levels impact adaptive capacity. Spatial agent-based modelling (SABM), enabled by growing computing power, has been successfully applied to analyse macro-outcomes in a virtual society, emerging out of the actions and interactions of individual heterogeneous agents in a city or region. Agent decision-making is flexible and incorporates behavioural factors, bounded rationality, interactions, and learning. Although SABM is actively used to study social, economic, and environmental problems, including CCA, they have not yet been used to explore the mutual dynamics of adverse climate impacts and poverty traps. You are expected to make methodological advancements in understanding the role of CCA in the emergence of poverty traps.

What are you going to do:

  • Develop and scale up a spatially explicit agent-based model to systematically explore the factors reinforcing poverty traps as climate change intensifies.
  • Perform sensitivity analysis of the model. Develop and implement strategies for model calibration and validation.
  • Collaborate with researchers at Red Cross Red Crescent Climate Centre to explore a wide range of real-world scenarios using the agent-based model.
  • Publish in high level international journals, presenting at leading conferences and collaborate with PhD/Master/Bachelor students.
  • Assure research data management following the FAIR data principles.
  • You will have the opportunity to contribute to policy reports and translating scientific evidence to practical recommendations.

The deadline to apply is 1 April 2022. Apply here: https://www.academictransfer.com/nl/306813/postdoctoral-researcher-on-the-impact-of-climate-adaptation-on-poverty-traps/

Postdoctoral Research Fellow in High-Performance Social Simulation (TU Delft)

Postdoctoral Research Fellow in High-Performance Social Simulation (TU Delft)

Postdoctoral Research Fellow in High-Performance Social Simulation (TU Delft)

TU Delft has an opening for a postdoctoral research fellow at the intersection of social simulation and high-performance algorithms.  The goal of project is to develop methods to speed large-scale agent-based modelling (ABMs), for example by means of effective parallelization using High Performance Computing (HPC).  The use of machine learning for efficient ABM simulations will enable uncertainty and global sensitivity analysis of large ensembles of ABM runs.  The postdoc will use the HPC cluster newly established at TU Delft in 2021.

The successful candidate will work closely with faculty members at the TU Delft faculties of Technology, Policy and Management, and Electrical Engineering, Mathematics and Computer Science.  Working with Prof Tatiana Filatova, Dr Jan Kwakkel and Dr Neil Yorke-Smith, the candidate will study how theory-informed meta-modelling and learned surrogate models can accelerate agent-based models.

This two-year position as a part of the EU project TAILOR (Foundations of Trustworthy AI, Integrating Reasoning, Learning and Optimization, tailor-network.eu) in conjunction with the TU Delft Institute for Computational Science and Engineering (DCSE, tudelft.nl/cse).  The TAILOR network is funded by the European Union to build the capacity of the scientific foundations for trustworthy AI in Europe, by developing a network of research excellence centres leveraging and combining learning, optimization and reasoning.  The successful candidate will have access to the TAILOR network, including travel and mobility funds.

The position is at the intersection of social simulation and high-performance algorithms, and links to two ongoing EU projects (TAILOR and ERC SCALAR).

Deadline for applications: 31 December 2021. Apply here:

 https://www.academictransfer.com/en/306558/postdoc-high-performance-social-simulation/apply/#apply

 

PhD position at UFZ Leipzig on “Modelling human-environment systems: How to effectively design climate risk instruments?”

PhD position at UFZ Leipzig on “Modelling human-environment systems: How to effectively design climate risk instruments?”

PhD position at UFZ Leipzig on “Modelling human-environment systems: How to effectively design climate risk instruments?”

In the POLISES group (www.polises.de) at the Helmholtz Centre for Environmental Research UFZ Leipzig, Germany, a three years PhD Position on  “Modelling human-environment systems: How to effectively design climate risk instruments?” is offered from April 1, 2022 on with a methodological focus on agent-based modelling.

The PhD project is embedded in the interdisciplinary project INSURANCEGRASS on “Assessment of formal, natural and social insurances: how to cope best with impacts of extreme events on grasslands for sustainable farming systems?”. In a consortium of agro-economists and grassland ecologists from ETH Zurich, biodiversity economists from IDiv Leipzig and social –ecological modellers at UFZ 4 PhD students will focus on sustainable grassland management systems in Germany and Switzerland. The deadline for application is December 15th, 2021.

Your tasks:

  • Develop a social-ecological simulation model (in particular agent-based model) that incorporates feedbacks between farmers’ and consumers’ decision, grassland management options, and ecosystem service provision in a dynamic matter
  • Parameterize the model with empirical data obtained in other work packages of the project
  • Contribute to a thorough understanding of how insurance products and policies should be designed to work effectively for farmers’ climate risk management and to promote sustainable grassland management
  • Use the model to explore the potential of social insurances, especially arrangements within community-supported agriculture and payments for ecosystem services.
  • Exchange knowledge with local and European stakeholders relevant in this research context (i.e., farmers, insurance companies, public administration)

Your profile:

  • An excellent master’s degree in a relevant field of research, including system sciences, mathematics, physics, agricultural economics, geography
  • Expertise in modelling and analyzing complex systems (experience in agent-based modelling is beneficial)
  • Proficiency in computer programming (e.g. NetLogo, C++, Java) and advanced statistical methods
  • Deep interest in investigating the impact of climate risk instruments (such as agricultural insurance or community supported agriculture) on farmers’ behavior and ecological state of the grassland system.
  • Excellent knowledge of spoken and written English and ambition to publish in international journals
  • High motivation to work in an international and interdisciplinary team
  • Readiness to travel within and beyond Europe to meet cooperation partners and attend conferences, workshops and courses

Apply here: https://recruitingapp-5128.de.umantis.com/Vacancies/2318/Description/2

Land Modeling and Data Assimilation System Specialist with SSAI at NASA Goddard Space Flight Center in Greenbelt, MD

Land Modeling and Data Assimilation System Specialist with SSAI at NASA Goddard Space Flight Center in Greenbelt, MD

Land Modeling and Data Assimilation System Specialist with SSAI at NASA Goddard Space Flight Center in Greenbelt, MD

Science Systems and Applications, Inc. is seeking a GEOS Land Modeling and Data Assimilation System specialist to support the Global Modeling and Assimilation Office at the NASA Goddard Space Flight Center. This position will begin in a telecommuting status with the eventual likelihood of a hybrid model with work on site at NASA’s GSFC.

The position is designed for a mid-career scientist/programmer or numerical modeler with commensurate experience using and/or running coupled atmosphere and land models. The selected staff member will contribute to the maintenance and development of the land modeling and data assimilation components of the Global Earth Observing System (GEOS) at the NASA Global Modeling and Assimilation Office (GMAO). This involves the following expected duties:

*   Develop, implement, and document, under advisement of civil service staff, improvements in the GEOS land modeling and data assimilation system.
*   Perform simulations with the stand-alone land model and with various configurations of the full GEOS Earth system model; process results as required.
*   Integrate science software and model parameters into the operational version of GEOS and perform associated tests.
*   Assist in solving daily technical problems (in addition to strictly scientific problems).
*   Ensure proper coordination with other model development groups in the GMAO.
*   Maintain appropriate standards and interfaces to facilitate coupling of land model and assimilation components into the broader NASA GEOS system.

Required Qualifications:

*   A minimum of an MS degree in numerical land, atmospheric, or ocean modeling or a related field.
*   6-10 years of experience in designing, running, and analyzing output from standalone or coupled land, atmosphere, or ocean numerical models or data assimilation systems
*   Extensive experience in FORTRAN or C/C++ programming is required
*   The applicant must be detail-oriented.

Desired Qualifications:

*   Experience in land surface hydrology and data assimilation preferred
*   Experience in Python programming is highly desired, as are familiarity with relevant data formats (including NetCDF and HDF), object-oriented software paradigms (e.g., ESMF), and software version control (e.g., git and github.com)
*   Expert knowledge of parallel computing processes and languages is also desired, as is a strong familiarity with graphics software.

NOTICE TO APPLICANTS:  As a federal contractor, all employees of SSAI are required to be vaccinated (by no later than December 8, 2021) unless eligible for a religious or health exemption.  Applicants selected for employment by SSAI must provide SSAI with the following documentation upon commencement of employment:

(a) a copy of the record of immunization from a health care provider or pharmacy, such as a copy of the COVID-19 Vaccination Record Card (CDC Form MLS-319813_r, published on September 3, 2020),

(b) a copy of medical records documenting the vaccination,

(c) a copy of immunization records from a public health or State immunization information system, or

(d) a statement that you are scheduled to receive a vaccination (identifying the date by which you expect to meet vaccination requirements).

The record must verify vaccination with information on the vaccine name, date(s) of administration, and the name of health care professional or clinic site administering vaccine.
Applicants seeking employment subject to a religious or health exemption should contact SSAI Human Resource Department.

SSAI is an Equal Employment Opportunity and Affirmative Action Employer.
EEO/AA-Minorities/Females/Veterans/Individuals with Disabilities

Apply here:
https://ssaihq.com/employment/Careers.aspx?req=21-3298&type=JOBDESCR