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 Data Scientist with expertise in data science 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 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 be responsible for working with biodiversity information standards for the content data streams in collaboration with project partners and international standards bodies.
- Contributing to the development, documentation, and curation of biodiversity data standards and vocabularies for ecological data and other relevant data types.
- Interact with task groups of the Biodiversity Information Standards (TDWG) community and other relevant stakeholders involved in the development of the biodiversity information standards required for the data streams to the BioDT.
- Capture requirements and coordinate collaboration on data standards from across the research infrastructures (RIs) of GBIF, Distributed System of Scientific Collections (DiSSCo ESFRI), Long-Term Ecosystem Research in Europe (eLTER ESFRI), and the LifeWatch ERIC.
- Developing and implementing processes and data flows from environmental databases to ecological models, including data quality and fitness for use checks.
- Disseminating captured project requirements and results from the improvement of the data standards at relevant conferences and in peer-reviewed scientific journals.
- Documenting and communicating data content and quality requirements, and addressing issues diagnosed in relation to the data standards.
- Collaborating with other team members at the GBIF Secretariat to mobilize new data resources through interactions with the biological community.
- Supporting RIs, data publishers, and data users with both technical and data standards-related questions.
- Supporting the wider network of RI partners and collaborators through technical support and training, including a strong communication component (email, video calls, etc.).
- A Ph.D. or an equivalent doctoral degree in data science, biodiversity informatics, ecoinformatics, natural sciences, or a related field.
- Research experience in biodiversity informatics and/or data science.
- Knowledge of research infrastructures for biodiversity information including the Global Biodiversity Information Facility (GBIF), Long-Term Ecosystem Research in Europe (eLTER), Distributed System of Scientific Collections (DiSSCo), and the LifeWatch ERIC e-Science European infrastructure for biodiversity and ecosystem research.
- Hands-on expertise with FAIR data principles, open science, open data stewardship, open data management, and open data publication best practices.
- Expertise in persistent identifier technologies.
- A relevant scientific publication record.
- Teaching experience within data science and/or biodiversity informatics.
- Excellent English language skills (written and spoken).
Desired qualifications and personal qualities
- Research experience with relevant biodiversity data standards including Darwin Core, Ecological Metadata Standards (EML), Biological Collections Ontology (BCO), Environment Ontology (EnvO), and/or Minimum Information about any (x) Sequence (MIxS).
- Research experience with relevant data types including primary biodiversity information, species occurrence data, collection specimens, taxonomic data, ecoinformatics, and ecological data.
- Experience with bioinformatics and/or DNA sequence data management.
- Experience with handling very large datasets (big data).
- Experience with working with relational database systems (RDBMS).
- Experience with suitable programming languages for data flow and analysis, including R, Python, PL/SQL, and/or SPARQL.
- Experience in programming and access to API interfaces.
- Experience with collaboration tools like Git (GitHub) and related solutions.
- Knowledge of high-performance computing (HPC).
- Knowledge of cloud computing environments and methodology.
- Demonstrated ability to communicate and work in a distributed team.
- Experience with teamwork in an international and multicultural setting.
- Scandinavian language skills are an advantage.
- Salary NOK 650 300 – 752 800 per annum depending on qualifications (Researcher, position code SKO 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.
- Career building links with a vibrant international research network with excellent opportunities for building a career in data science.
- 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 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.
The application with attachments must be delivered in our electronic recruiting system.
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.
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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.