Job description

Position as PhD Research Fellow in signal processing and acoustic beamforming available at Digital Signal Processing and Image Analysis group (DSB)Section for Machine LearningDepartment of InformaticsUniversity of Oslo.

The DSB research group has six full-time and seven adjunct positions. We perform research over a wide range of applications in image analysis and deep learning, as well as in digital signal processing/acoustic imaging. There are about 20 Postdocs and PhD students in the group with financing from a variety of national and international funding agencies, as well as from industry.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Starting date no later than October 1, 2022.

The fellowship period is three (3) years. Candidates may be offered one additional year by the Department of Informatics; the four (4) year position then entails a compulsory workload of 25% that may consist of teaching, supervision duties, and research assistance. This will be decided at the time of appointment.

Foto: Colourbox

More about the position

This position is funded by the Smart AUVs project (Smart AUVs for detection and characterization of greenhouse gas emissions in the oceans, funded by the Research Council of Norway). The position is placed with the DSB group at the University of Oslo, which has its offices in the Ole-Johan Dahl Building, close to the Forskningsparken metro and tramway station in Oslo.

The Smart AUVs project aims to significantly improve the effectiveness of autonomous underwater vehicles (AUVs) for marine monitoring by developing intelligent algorithms allowing the vehicle to adjust its travel path and data acquisition scheme in real time based on sensor measurements. Norway is investing heavily in full-scale carbon capture, transport and storage. A key aspect in the Smart AUVs project is to strengthen the confidence in safe carbon dioxide (CO2) storage, as well as to gain further insights into the amount of methane (CH4) entering the oceans through natural- and industry related processes.

The research focus of this position is signal processing to develop intelligent algorithms for automatic detection and characterization of greenhouse gas seepage in the oceans, based on acoustic sensor data. The PhD fellow should evaluate existing methods and develop new ones for automatic gas bubble detection, considering both AI approaches and traditional (non-AI) algorithms. Successful algorithms will be implemented into the internal processing unit of the HUGIN AUV and demonstrated during field trials. The work will build on previous work carried out at the DSB research group on beamforming and on know-how developed in previous projects conducted at NGI (the Norwegian Geotechnical Institute).

Through Smart AUVs, a larger dataset will be available. The PhD candidate will collaborate closely with the research- and industry partners of Smart AUVs. The candidate is expected to publish research results in international peer-reviewed journals in collaboration with the DSB group and its research partners. A detailed research plan for the PhD period will be elaborated based on both the project objectives and the candidate’s background.

NGI is an international centre for applied research and consultancy in geosciences with many years of experience within marine environmental monitoring, and is the coordinator for the Smart AUVs project. NGI has its main headquarters at Nydalen in Oslo, with approximately 350 employees.

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 this fellowship will be selected in accordance with this, and they are expected to be in the upper segment of their class with respect to academic credentials.

Required qualifications:

  • Applicants must hold a Master’s degree or equivalent in signal processing, physics, applied mathematics, electrical engineering, cybernetics, data science, computational science, or related fields. Foreign completed degrees (M.Sc.-level) must correspond to a minimum of four years in the Norwegian educational system.
  • Proficiency in scientific programming (Python / Matlab / Julia / R / bash)
  • Strong skills in signal processing
  • Willingness to be part of a team and to share knowledge and skills
  • Ability to communicate science
  • Strong writing skills
  • Spoken and written fluency in the English language

Candidates without a Master’s degree have until 30 June, 2022 to complete the final exam.

The following are also desirable:

  • Experience in acoustic and/or array-based imaging modalities (sonar, ultrasound, seismics, radar, array seismology, etc.)
  • Experience with signal processing and adaptive beamforming, wave propagation simulation, filter design, numerical methods, mathematical modelling, linear algebra, statistics
  • Acoustical theory knowledge
  • Experience in analysis of experimental data
  • Laboratory work experience

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
  • 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

The purpose of the fellowship is research training leading to the successful completion of a PhD degree.

The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position.

For more information see: 
http://www.uio.no/english/research/phd/
http://www.mn.uio.no/english/research/phd/

Personal skills

We look for an enthusiastic self-motivated candidate who can work efficiently both in group and individually.
We expect:

  • A passion for signal processing, scientific programming, problem solving, data science, and visualization.
  • Ability to carry out and complete major tasks.
  • Collaborative skills and willingness to share knowledge, information and to support others in the pursuit of team goals.

We offer

  • Salary NOK 501 200 – 544 400 per year depending on qualifications and seniority as PhD Research Fellow (position code 1017)
  • Attractive welfare benefits and a generous pension agreement
  • Vibrant international academic environment
  • Career development programmes
  • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

How to apply

The application must include the following 6 attachments, in PDF format:

  • Cover letter, including a statement of motivation and research interests, as well as a description of the relevance of your MSc in relation to this project, signal processing and acoustical beamforming
  • CV (summarizing education, positions, and academic work)
  • 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)
  • Copies of the original Bachelor and Master’s degree diploma, transcripts of records
  • Documentation of English proficiency

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.

Applicants will be called in for an interview.

Formal regulations

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

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

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.

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

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.

Contact information

For further information please contact:

Associate Professor Sven Peter Näsholm, phone: +47 22840068 / +47 93834349, e-mail: svenpn@ifi.uio.no or
Professor Andreas Austeng, phone: +47 22852741, e-mail: andreas.austeng@ifi.uio.no

For technical questions regarding the recruitment system, please contact HR Adviser Therese Ringvold, e-mail: therese.ringvold@mn.uio.no

About the University of Oslo 

The University of Oslo is Norway’s oldest and highest rated institution of research and education with 28 000 students and 7000 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society. 

The Department of Informatics (IFI) is one of nine departments belonging to the Faculty of Mathematics and Natural Sciences. IFI is Norway’s largest university department for general education and research in Computer Science and related topics. 

The Department has more than 1800 students on bachelor level, 600 master students, and over 240 PhDs and postdocs. The overall staff of the Department is close to 370 employees, about 280 of these in full time positions. The full time tenured academic staff is 75, mostly Full/Associate Professors.

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