With about 16,000 students, Western Norway University of Applied Sciences is one of the largest higher education institutions in Norway. A broad range of academic programmes are offered at Bachelor, Master and PhD levels, spread out on five campuses Førde, Sogndal, Bergen, Stord og Haugesund.
Our ambition is to build stronger and more solid academic and research environments that will interact nationally and internationally. The aim is to become a recognized actor on the international higher education arena. Increased international cooperation and engagement in externally funded projects will work towards this goal.
The Faculty of Engineering and Science has approximately 300 employees and approximately 3,200 students. The faculty has a broad educational offer at both bachelor's and master's level in engineering and science, as well as PhD education in computer technology. The Mohns Center for Innovation and Regional Development researches innovation and offers master's education in innovation and entrepreneurship. The diving education offers a one-year vocational school education.
The main part of the faculty's activities are in Haugesund, Bergen, Sogndal and Førde, but we also offer education in Stord.
The faculty's activities are internationally based and take place in close collaboration with regional companies, clusters, health trusts and the public sector, including other institutions in the university and college sector. This applies to research, development, innovation and not least education with student projects at all levels.
A full time (100%) position as a postdoctoral fellow for a period of 3 years is available at Western Norway University of Applied Sciences, Faculty of Engineering and Science.
We are looking for a highly motivated and talented postdoctoral research fellow to be part of the Bergen particle physics group. The position is associated with the research project “Use Artificial Intelligence to pinpoint dark matter at the LHC” financed by the Research Council of Norway, and is for a fixed-term period of 3 years. If you are interested in machine learning and the search for dark matter in the ATLAS experiment at CERN, this position could be something for you.
About the project/work tasks
The current paradigm change in computer science based on artificial intelligence (AI), combined with a large increase in data volume from the upcoming Run3 of the Large Hadron Collider at CERN, open up unprecedented opportunities to shed light upon the long standing mystery of dark matter. With this project, you will work on developing new search strategies for dark matter candidates in data from the ATLAS experiment at the Large Hadron Collider using supervised and semi-supervised machine learning techniques, targeting the phase space of soft tau leptons.
Tau leptons are complicated objects to work with in a hadron collider experiment, due to their short lifetime. Nevertheless, the tau lepton sector may be exactly where the dark matter hides. With this project, we will therefore also investigate if and how we can improve the reconstruction and identification of tau leptons with low transverse momentum in the ATLAS experiment.
Although powerful, machine learning algorithms are opaque, and the concern that we do not fully understand the underlying decisions made by these so-called black-box algorithms is very much justified. The huge and complex data analysis setting of the ATLAS experiment enables questioning and interpreting AI decision taking. Furthermore, it allows us to analyse how the use of AI is influencing our traditional critical and analytical thinking mindsets. Along with applying supervised and semi-supervised machine learning techniques in the search for dark matter, this project will seek to develop reliable and interpretable AI models.
You will also be encouraged to take part in the supervision of MSc and PhD candidates.
Research environment
The Bergen particle physics group is a close collaboration between researchers at Western Norway University of Applied Sciences and University of Bergen. The group has a long history in ATLAS and has contributed to several analyses, recently focusing mostly on search for supersymmetric models with relevance for dark matter candidates, and Higgs boson physics. Most of the analyses concern final states which include one or more tau leptons, and the group is also a major contributor to the tau working group.
The part of the group located at Western Norway University of Applied Sciences has a particular focus on use of machine learning methods both in event reconstruction and physics analysis. As a part of the Department of Computer Science, Electrical Engineering and Mathematical Sciences we are also in close contact with machine learning experts working outside of physics.
For this particular project, we are in the process of hiring two new PhD candidates and one postdoctoral researcher to work closely together as a team together with the project group to solve the tasks described above. We will have regular meetings in the project group and with the extended Bergen particle physics group. You will also be part of the newly established Norwegian Centre for CERN research, ensuring good contact with other particle physics groups in Norway.
The position is located in Bergen, with the possibility for research visits to CERN.
Qualifications and personal qualities:
We seek a highly motivated postdoctoral researcher with experience applying machine learning to problems in particle physics.
The candidate must hold a PhD-degree within the field of particle physics or have submitted their doctoral dissertation for evaluation within the closing date of the application. It is a condition for appointment that the dissertation is approved.
The candidate must have research experience in use of machine learning techniques applied to problems in particle physics, e.g. object reconstruction or physics analysis.
In your application you have to point out why you are especially motivated and qualified for this particular position. We are looking for candidates who have experience in both machine learning and data analysis in particle physics.
Very good programming skills is a requirement. You are encouraged to include a link to your GitHub profile or similar documentation of programming competence in your application.
The candidate should be proficient in spoken and written English.
About the position of postdoctoral research fellow:
The postdoctoral position is a fixed term position with the primary objective of qualifying the appointee for work in top academic positions. If the appointee is interested, and if the institution is in need of additional teaching staff, the employment period may be extended up to 4 years. Teaching and other duties will in such cases be added to the position. The position may be extended by up to one year (maximum 4 years in total) if the appointee is granted externally financed research stays abroad. Individuals may not be hired for more than one fixed-term period as a postdoctoral research fellow at the same institution. The completion of the project proposal for the qualifying work, as well as a progress plan, will be developed in cooperation with the supervisor and head of department. It is a requirement that the project is completed in the course of the period of employment.
Application procedure:
Applications will be evaluated by an expert panel consisting of three members. Applicants are asked to submit their application and CV online. Please use the link “Apply for this job” (“Søk stillingen”).
The following documentation must be uploaded as an attachment to the online application:
CV with a complete list of academic publications
Cover letter highlighting qualifications and motivation for applying for this particular position
Diplomas and certificates
Copies of selected academic publications (no more than 5)
At least two reference/recommendation letters
Applicants should indicate which publications or parts of publications should be given special consideration in the evaluation. If the documents submitted are not in a Scandinavian language or in English, applicants must submit certified translations of these
Applicants should note that the evaluation will be based on the documentation submitted electronically via Jobbnorge within the submission deadline. The applicants are responsible for ensuring that all the documentation is submitted before the closing date. It is of utmost importance that all publications to be considered in the evaluation are uploaded as an attachment with the application, since these are sent electronically to the expert panel. Applications cannot be sent by email or to individuals at the college.
Start date is as soon as possible, and no later than January 1st 2022.
Salary:
Good occupational pension, insurance and loan schemes from The Norwegian Public Service Pension Fund
Exciting academic environment with the possibility of competence enhancement and development
Opportunities for training within the working hours
The position as Postdoctoral Reseach Fellow is paid according to the Government's salary regulation, in position code 1354 -Postdoctor.
There is a compulsory 2 % deduction to the pension fund (see http://www.spk.no for more information). The successful applicant must comply with the guidelines that apply to the position at any time.
General information:
The appointment will be made in accordance with the regulations for State employees Law in Norway ("Lov om statens ansatte)". Organizational changes and changes in the duties and responsibilities associated with the position must be expected.
State employment shall reflect the multiplicity of the population at large to the highest possible degree. Western Norway University of Applied Sciences Bergen has therefore adopted a personnel policy objective to ensure that we achieve a balanced age and gender composition and the recruitment of persons of various ethnic backgrounds.
Information about the applicant may be made public even though the applicant has requested not to be named in the list of applicants. The applicant will be notified if his/her request is not respected.
Short-listed applicants will be called in for an interview.
For further details about the position, please contact:
Therese Sjursen, Department of Computer Science, Electrical Engineering and Mathematical Sciences,
