About the position

Position as Researcher available at the Department of Geosciences.

The position is externally financed, current financing exists for a period of 4 years.

Starting date preferably no later than October 15th 2024.

The position aims to develop actively learning observing systems for land-atmosphere fluxes of carbon, water, and energy in arctic environments. To this end, the project will build a probabilistic framework around modern land-surface models (such as the Community Land Model) to enable Bayesian inference of model parameters. Observations from eddy flux towers, drone swarms carrying meteorological sensors and gas analyzers, as well as satellite remote sensing products will be central for this purpose. The uncertainty-aware model predictions will be used in active learning frameworks to iteratively adapt the design of this observing system to make future observations maximally informative for critically unconstrained processes on the land surface.

The work will build on the existing infrastructure at the Department of Geosciences, including data assimilation frameworks, and an observing system with mobile flux towers and drones. Fieldwork for testing newly developed algorithms is anticipated in mainland Norway, Svalbard, and abroad.

Funding is also available for conference attendances and research visits with external collaborators.

The position is part of the ERC Starting Grant “Actively learning experimental designs in terrestrial climate science (ACTIVATE)”.

The researcher will be part of a growing team of researchers, postdocs and PhD students working on intelligent observing systems using machine learning and data assimilation methods in the ACTIVATE project. 

Qualification requirements:

The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe's leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

• Applicants must hold a degree equivalent to a Norwegian doctoral degree in geosciences, environmental sciences, computer/data science, mathematics, or any other relevant field. Only applicants with an approved doctoral thesis and public defence are eligible for appointment.
• The candidate must have a strong quantitative background and extensive experience in scientific programing (using e.g., Python, Matlab, and/or Julia), as well as a strong interest in climate science and biogeochemical cycling.
• The candidate must have proof of excellence in research as demonstrated through publications in refereed journals and presentations at scholarly conferences. The candidate’s publication record must show evidence of creativity and capability of independent research.
• An excellent command of written and spoken English is required.
• Applicants must be able to work independently while having the ability to actively communicate and co-operate within the larger research team.

The following qualifications are desirable:

• Previous experience applying Bayesian inference, data assimilation, inverse modeling, and/or probabilistic machine learning to geoscientific or ecological models is highly desirable. 
• Experience in high performance computing and handling of large data sets such as Earth observations are an advantage.

We offer:

• Salary NOK minimum 575 400 – 657 300 per annum depending on qualifications in position as Researcher (position code 1109)
• Attractive welfare benefits and a generous pension agreement
• Professionally stimulating working environment
• Vibrant international academic environment
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

The application must include:

• Cover letter (statement of motivation, summarizing scientific work and research interest)
• CV (summarizing education, positions, pedagogical experience, administrative experience and other qualifying activity)
• Copies of educational certificates, academic transcript of records and letters of recommendation
• A complete list of publications and up to 5 academic works that the applicant wishes to be considered by the evaluation committee
• Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

The application with attachments must be delivered in our electronic recruiting system, please follow the link “Apply for this job”. Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English (or a Scandinavian language).

In assessing the applications, special emphasis will be placed on the documented, academic qualifications, as well as the candidates motivation and personal suitability. Interviews with the best qualified candidates will be arranged.

It is expected that the successful candidate will be able to complete the project in the course of the period of employment.

Formal regulations:

According to the Norwegian Freedom and 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.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results a.o.

The University of Oslo aims to achieve a balanced gender composition in the workforce and to recruit people with ethnic minority backgrounds.

The position is considered to be subject to regulations for export control and sanctions. Applicants for the position must meet all necessary employment permits at lasted by the stated start date. Applicants with one or more foreign citizenships must list all of these in the application. This also applies to applicants who simultaneously hold Norwegian citizenship.

Contact persons:

For further information about the position please contact:

•  Norbert Pirk, phone: +47 228 58455, e-mail: norbert.pirk@geo.uio.no 

For technical questions regarding the recruitment system please contact: HR-adviser Ole Rustad, e-mail: ole.rustad@mn.uio.no

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