PhD Research Fellow in the Development of actively learning observing systems

Arbeidsgiver
Universitetet i Oslo
Stillingstittel
PhD Research Fellow in the Development of actively learning observing systems
Frist
28.02.2025
Ansettelsesform
Prosjekt

Beskrivelse

About the position

Position as PhD Research Fellow in the Development of actively learning observing systems available at the Department of Geosciences, Faculty of Mathematics and Natural Sciences, University of Oslo.

The fellowship period is 3 years.

Starting date no later than October 1st 2025.

A fourth year may be considered with a workload of 25 % that may consist of teaching, supervision duties, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.


Project description and work tasks

The PhD fellow will contribute to the development of an observing system for land-atmosphere fluxes of carbon, water, and energy in arctic environments. Observations from eddy flux towers, drones carrying meteorological sensors and gas analyzers, soil sensors, and satellite imagery are fused with land-surface models such as CLM using data assimilation. The goal is to develop an adaptive experimental design framework for the observing system to guide ongoing measurement campaigns and targeted, computationally expensive, model simulations. This experimental design process is envisioned to update iteratively as new data become available to optimally infer surface fluxes across the landscape.

The work will build on and extend the existing infrastructure at the Department of Geosciences, including mobile flux towers and drone-based observing systems developed in-house.

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-funded project “Actively learning experimental designs in terrestrial climate science (ACTIVATE)”:
https://www.mn.uio.no/geo/english/research/projects/activate/index.html

The PhD fellow 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. 


Qualifications 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.

Required qualifications

  • Master’s degree or equivalent in geosciences, mathematics, computer/data science, physics, environmental sciences, or any other relevant field.
  •  Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system
  •  The candidate must have a strong quantitative background including experience in scientific programing (using e.g., Python, MATLAB, R, or Julia)
  • A strong interest in land-atmosphere interactions, data assimilation methods, and land-surface modelling are required.

Desired qualifications

  • Experience with data assimilation, probabilistic machine learning, Bayesian inference, inverse modeling, and/or simulation-based inference is an advantage.
  • Experience with land-surface models, micro-meteorology, Earth system modeling, and/or satellite remote sensing is an advantage.
  • Experience with fieldwork in challenging environments is an advantage
     

Language requirement

  • Fluent oral and written communication skills in English
  • English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements:

https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8

Grade requirements

The norm is as follows:

  • the average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
  • the average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
  • the Master’s thesis must have the grade B or better in the Norwegian educational system

Candidates without a master’s degree have until 30 June 2025 to complete the final exam.

The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see:  http://www.mn.uio.no/english/research/phd/


Personal skills

Applicants must be able to work independently while having the ability to actively communicate and co-operate within the larger research team.


We offer
  • Vibrant international academic environment
  • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities
  • Good welfare schemes.
  • Career development programmes
  • Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes.
  • Salary in position as Doctoral Research Fellow, position code 1017, in salary range NOK from 536 200 - 575 400, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund.

Read more about the benefits of working in the public sector at Employer Portal.


Inclusive worklife and diversity at UiO

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.

We hope that you will apply for the position. 

More information about gender equality initiatives at UiO can be found here.


Application

The application must be submitted as a single PDF and include:

  • Cover letter - statement of motivation and research interests
  • CV (summarizing education, positions and academic work - scientific publications)
  • Copies of the original Bachelor and Master’s degree diploma, transcripts of records and 
  • Documentation of English proficiency
  • List of publications and academic work 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)

Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for the position".

When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language. Foreign applicants should attach an official explanation of their University's grading system.


General information

The best qualified candidates will be invited for interviews. 

Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us.

Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian),  Guidelines concerning appointment to post doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo.

The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.


Sektor
Offentlig
Sted
Problemveien 7, 0313 Oslo
Stillingsfunksjon
Forskning/Stipendiat/Postdoktor, Ingeniør, Annet
FINN-kode
391357752
Sist endret
31. jan. 2025 10:27