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.
There is a vacancy for a PhD Research Fellow (PhD position) in particle physics at the Department of Computer science, electrical engineering and mathematical sciences at Western Norway University of Applied Sciences (HVL).
We are looking for a highly motivated and talented PhD research fellow to be part of the Bergen particle physics group. The position is part of 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.
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 weekly meetings in the project group and meet bi-weekly 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 the particle physics community in Norway.
The position is located in Bergen, with the possibility for research visits to CERN.
Qualifications and personal qualities:
Applicants must hold a master's degree or equivalent education in particle physics, or closely related fields, or must have submitted his/her master's thesis for assessment prior to the application deadline. It is a condition of employment that the master's degree has been awarded.
Research experience in high-energy physics is a requirement, for example, from work on a master's thesis.
Experience from data analysis within the ATLAS or CMS experiments is a strong advantage.
Applicants must be proficient in both written and oral English .
Personal skills will be emphasized. The candidate should be able to work independently and interactively in a team setting, be motivated and responsible, and also have a great work capacity and enthusiasm for research, including writing manuscripts.
Other aspects that will be taken into consideration in the selection process:
Experience from work in a large research collaboration.
Knowledge of the ATLAS detector and software environment.
Experience in machine learning.
Interest in tau-lepton physics and reconstruction
About the research training
As a PhD Research Fellow, you must participate in an approved educational programme for a PhD degree within a period of 3 years. The deadline for applying for admission to the PhD programme at The University of Bergen, Faculty of Mathematics and Natural Sciences is 2 months after you start your position or after the start of the research project that will lead to the PhD degree. It is a condition that you satisfy the enrolment requirements for the PhD programme at the University of Bergen.
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
Transcripts and diplomas showing completion of the bachelor's and master's degrees. If you have not yet completed your master's degree, please submit a statement from your institution confirming the expected date of award of your master's degree. Your master's degree must be documented with transcripts and/or diploma, alternatively a confirmation from your institution on completed degree and your grade, by 15.09.2021
Copies of selected academic publications (no more than 3)
Copy of master's thesis
Names and contact information for two referees. One of these should be the main advisor for the master's thesis or equivalent thesis
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
Initial salaries will be offered at grade 54 (code 1017) in the Civil Service pay grade table scale.
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:
