For the HORIZON-INFRA-2021-TECH-01 project "Biodiversity Digital Twin for Advanced Modeling, Simulation, and Prediction Capabilities" (BioDT) the University of Oslo is looking for a researcher with expertise in ecology, ecoinformatics, and biodiversity informatics. The BioDT project is a 36-month (2022-2025) pan-European research infrastructure project coordinated by the CSC IT Center for Science (Espoo, Finland) and includes 22 project partners from across 12 countries. GBIF, represented by the GBIF Secretariat and GBIF Norway at UiO, lead work package 4 on data content streams.
More about the position
The appointment is a full-time, 2.5-year position planned to start in the third quarter of 2022. The position will be associated with the Norwegian Participant Node (GBIF Norway) of the Global Biodiversity Information Facility (GBIF) and based at the University of Oslo Natural History Museum in Oslo. The appointed candidate will take part in a multinational team for delivering the responsibilities of UiO for the Horizon Europe-funded Biodiversity Twin (BioDT) project and will be responsible for UiOs contribution to the scientific use cases.
The BioDT includes 8 scientific use cases designed to act as tools to calibrate and ensure that the digital twin simulation model is fit for providing a relevant research environment. Use cases 1 on biodiversity dynamics and 2 on ecosystem services are designed to validate that the BioDT can answer scientific questions related to species' responses to environmental change. Use cases 3 on crop wild relatives and genetic resources for food security and 4 on DNA detected biodiversity in poorly known habitats including soil are designed to validate BioDT fitness for scientific research on genetically detected biodiversity. This position will lead the delivery of use case 3 research and contribute to the other use cases. Use cases 5 on invasive species and 6 on endangered species will validate BioDT fitness for research on dynamics of species of special or policy concern. Use cases 7 on disease outbreaks and 8 on pollinators validates the BioDT for research questions on the influence of species interactions on planetary well-being.
- Research contributing to the scientific use cases to demonstrate the fitness of the Digital Twin model for facilitating research.
- Capture the fitness of use for the BioDT model to facilitate research and work with other project teams to improve this fitness.
- Collaborate with the GBIF Secretariat to design and carry out use cases on genetically detected biodiversity and on the influence of species on planetary well-being.
- Lead the scientific work for use case 3 on crop wild relatives and genetic resources for food security.
- Disseminating results from the use cases at relevant conferences and in peer-reviewed scientific journals.
- Documenting and communicating data content and quality requirements, and addressing issues diagnosed with data content.
- Collaborating with other project teams to mobilize new data resources.
- Explore potential gaps in data coverage in the data streams entering the BioDT and work together with the project team and the European biodiversity research data infrastructures to mobilize data and address data gaps through interactions with the biological community.
- Explore potential gaps or issues of the biodiversity standards in facilitating the relevant data streams into the BioDT to support the use cases and support the project team in improving the data standards.
- Contributing to the development, documentation, and curation of guidelines and training materials for how to use the BioDT for research and for teaching.
- Supporting data publishers and data users with both scientific, technical, and data content-related questions as well as the wider network of BioDT collaborators.
- A Ph.D. or an equivalent doctoral degree in ecology, ecoinformatics, data science, biodiversity informatics, natural sciences, or a related field.
- Research experience in ecology, ecoinformatics, and/or biodiversity informatics related to the topics of the BioDT scientific use cases.
- A relevant scientific publication record.
- Expertise with FAIR data principles, open science, and open data management.
- Knowledge of, and preferably experience with, data handling of large amounts of data.
- Knowledge of, and preferably experience with, suitable programming languages for data flow and analysis, including R, Python, PL/SQL, and/or SPARQL.
- Basic knowledge of Linux or Unix-like systems.
- Experience with high-performance computing (HPC).
- Excellent English language skills (written and spoken).
Desired qualifications and personal qualities
- Knowledge of research infrastructures for biodiversity information including the Global Biodiversity Information Facility (GBIF), Long-Term Ecosystem Research in Europe (eLTER ESFRI), Distributed System of Scientific Collections (DiSSCo ESFRI), and the LifeWatch ERIC e-Science European infrastructure for biodiversity and ecosystem research.
- Teaching experience within data science and/or biodiversity informatics.
- Experience with relevant data including primary biodiversity information, species occurrence data, taxonomic data, ecoinformatics, and ecological data.
- Research experience with the topics of the BioDT scientific use cases (1) biodiversity dynamics, ecosystem services, and/or species responses to environmental change (2) crop wild relatives and/or plant genetic resources (3) DNA detected biodiversity in poorly known habitats including soil (4) invasive species, endangered species, disease outbreaks, and/or pollinators in the context of planetary well-being.
- Experience with cloud computing environments and methodology.
- Expertise in working with relational database systems (RDBMS).
- Experience in programming and access to API interfaces.
- Experience with collaboration tools like Git (GitHub) and related solutions.
- Demonstrated ability to communicate and work in a team.
- Experience with teamwork in an international and multi-cultural setting.
- Experience with coordinating international teams, seminars, and workshops.
- Scandinavian language skills are an advantage.
- Salary NOK 650 300 - 752 800 per annum depending on qualifications (Researcher, position code 1109).
- A chance to contribute to building a world-class research infrastructure that is central to the European strategic plans for research, digitization, and green new deal.
- A chance to work with the EuroHPC LUMI supercomputer with a GPU with over 550 PFlop/s, 194.560 cores, ranking as the 76th most powerful non-distributed computer system in the world.
- Excellent technical facilities which are without parallel.
- Career building links with a vibrant international research network with excellent opportunities for building a career in data science and/or ecoinformatics.
- A stimulating and friendly working environment.
- Membership in the Norwegian Public Service Pension Fund.
- Attractive welfare benefits and a generous pension agreement, in addition to Oslo’s family-friendly environment with its rich opportunities for culture and outdoor activities.
How to apply
The application must include:
- A cover letter that includes a statement of motivation and a summary of scientific background and research interests.
- A CV summarizing education, positions, research profile and merits, pedagogical qualifications, and other qualifying activities.
- A list of all scientific publications.
- Contact information for two reference persons (name, relation to candidate, e-mail, and phone number). No reference letters should be submitted.
- The application with attachments must be delivered in our electronic recruiting system.
- Please note that all documents should be in English. Interviews will be part of the appointment process.
According to the Norwegian Freedom of Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.
Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience, and perspectives.
If there are qualified applicants with disabilities, employment gaps, or immigrant background, we will invite at least one applicant from each of these categories to an interview.
Chief engineer Dag Endresen, email@example.com, +47 40612982, https://orcid.org/0000-0002-2352-5497
Professor Olav Skarpaas, firstname.lastname@example.org, +47 99294394, https://orcid.org/0000-0001-9727-1672
Research Director Hugo de Boer, email@example.com, +47 98126030, https://orcid.org/0000-0003-1985-7859
For questions about the recruitment system, please contact HR-Officer Thomas Brånå: firstname.lastname@example.org
About the University of Oslo
The University of Oslo (https://ror.org/01xtthb56) is Norway’s oldest and highest ranked educational and research institution, with 28 000 students and 7000 employees. With its broad range of academic disciplines and internationally recognised research communities, UiO is an important contributor to society.
The Natural History Museum (http://www.wikidata.org/entity/Q1840963) has about 160 employees organized into five sections. The section for research and collections has about 80 employees, organized into nine research groups, and conducts research in biodiversity and evolution. The research covers both biology and geology (incl. paleontology), and the scientific staff is responsible for managing and developing the largest scientific collection in Norway (approx. six million objects). NHM's scientific staff also contributes by teaching and supervising students admitted to various programs at the Faculty of Mathematics and Natural Sciences and disseminates research-based knowledge to the public through exhibitions, lectures, and popular science media.
The Global Biodiversity Information Facility (GBIF), (https://ror.org/05fjyn938) is an international network and data infrastructure funded by the world’s governments and aimed at providing anyone, anywhere, free and open access to data about all types of life on Earth. The Norwegian Participant node in GBIF (www.gbif.no) is hosted at the UiO-NHM.
Deadline: 7th August 2022
Employer: University of Oslo
Duration: Project (project end is May 2025)
Place of service: Oslo