PhD Research Fellow in Advanced Computational Methods for Treatment Verification in Proton Therapy
Deadline: 08.02.2024
Publisert
Western Norway University of Applied Sciences
With about 17,500 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 370 employees and approximately 3,260 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 decentralized education in Florø, Kristiansund and 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.
The Department of Computing, Mathematics and Physics at Western Norway University of Applied Sciences, has a vacancy for a research fellow (PhD position) in advanced computational methods for treatment verification in proton therapy.
The fellow will be part of the Horizon Europe project “NOVO: Next generation imaging for real-time dose verification enabling adaptive proton therapy” and will join an international team of experts at the intersection of proton therapy, computer science, applied mathematics, detector physics and medical physics.
The PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing. The research programme in Computer Science currently includes 20 professors and associate professors, 25 PhD and post-doctoral fellows, and a large number of master’s students.
About the PhD project:
Proton therapy has the potential to offer the most conformal radiation dose to patients, and the number of proton therapy centers around the globe follows a significantly upwards and persisting trend. Adaptive proton therapy, by monitoring and adapting to changes in patient anatomy between treatment fractions, is required to enable safe delivery of proton therapy and to spare healthy tissues. However, truly personalised, dose escalated treatments with proton therapy are not yet possible due to the lack of real-time dose verification technology to truly empower patient-centered cancer treatment, important to improve curation and quality-of-life.
The NOVO (Next generation imaging for real-time dose verification enabling adaptive proton therapy) project aims at making real-time dose verification an integral component of proton therapy -based cancer care in the long-term, allowing precise control over radiation doses delivered to the tumor, as well as preventing unintended exposure of healthy surrounding tissues. We will develop the first proof-of-concept of a groundbreaking real-time dose verification technology adaptable to any proton therapy treatment. The proof-of-concept will be tested under pre-clinical conditions, bringing the envisaged technology concept to Technology Readiness Level 4.
Starting in March 2024 for a duration of four years, NOVO will receive European Union’s funding of almost 3.8 million € from the European Innovation Council as part of the EIC Pathfinder Open program, under Horizon Europe. EIC Pathfinder supports the exploration of bold ideas for radically new technologies and finances high-risk / high gain and interdisciplinary cutting-edge science collaborations for technological breakthroughs.
In this project, the PhD candidate will be working in Work Packages 2 (Image reconstruction & AI-enhanced modelling) and 3 (Dose reconstruction in clinical settings) and will collaborate with international and national experts on AI, image reconstruction and proton therapy. More specifically, the PhD candidate will be expected to work on the development of a cycle consistent adversarial network or cycle Generative Adversarial Networks to predict phase spaces of secondary particles of relevance i.e., fast neutrons and prompt gamma-rays in computational phantoms. The candidate will also develop deep learning models that can be trained with highly accurate Monte Carlo type data to automatically predict the detector response for a given source distribution. Furthermore, the candidate will be expected to develop AI models for image reconstruction where Bayesian Physics Informed Neural Networks will be considered for the detector domain whereas Deep Image Prior Networks will be considered for the image domain. In addition to this, the candidate will work on modeling voxel-wise hypoxia using prompt gamma-ray energy spectroscopy where novel analysis techniques such as Monte Carlo Library Least Squares will be in focus. Finally, the feasibility of incorporating all methods developed by the candidate into a real-time adaptive proton therapy system will be explored in close collaboration with project partners and stakeholders.
Research environment
The computer science research environment at Western Norway University of Applied Sciences (HVL) has a strong focus on use-inspired and applied research, and on ICT as an enabling technology. The research environment has cooperation with many national and international research groups, and with national and regional industry partners. The programme includes the research themes of software engineering, engineering computing, communication systems and sensor networks, grid computing and physics data analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with our current PhD students in the intersection of health, innovation, and technology.
The PhD-candidate will work closely with the staff members involved in the NOVO project at HVL. The candidate will further benefit from working together with national and international colleagues with expertise in detector physics, electronics, AI, machine learning, clinical proton therapy and radiobiology. The candidate will also collaborate with relevant stakeholders in the project, including relevant staff and project partners at the upcoming proton therapy center in Bergen, Norway.
The PhD-candidate will receive an annual stipend to be used for conference participation, research visits as well as participation in the annual project workshops. The candidate is expected to spend 3-6 months abroad at an international academic institution during the PhD-project. The academic institution is expected to be one of the project beneficiaries.
Qualifications:
The PhD research fellow must hold a master's degree in computer science, applied radiation, nuclear and/or medical physics, AI and machine learning, applied mathematics or in a closely related field, and have a strong emphasis on computational tasks. Candidates who have submitted a master’s thesis (but who has not yet been awarded a master’s degree) may also qualify for the position provided that the master`s degree is awarded within 4 weeks after the application deadline. A solid background in Monte Carlo type radiation transport calculations, advanced programming skills, AI and machine learning techniques will be considered an advantage when candidates are ranked. Candidates already holding a PhD within this field are not eligible for this position.
In addition to the required educational and scientific background, the following criteria will be evaluated: competence and grades on completed course work, quality of the master's thesis (excellent grade, equivalent of grade B or better on the ECTS grading system), publications (if any), research and teaching experience, practical software engineering skills and experience. A possible outline of a research plan for a potential PhD project will also be taken into account.
The candidate must be diligent and display the ability to work independently, supplemented with regular guidance, and is expected to carry out high-quality research and to publish the results in international workshops, conferences, and journals.
The PhD research fellow must enrol in the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing at Western Norway University of Applied Sciences and must meet the formal admission requirements for admission into the PhD programme. An application for enrolment should be first submitted after an appointment is made and the supervisor(s) will help with this procedure. The candidate must be enrolled as a PhD student within 3 months from the start of the employment.
The position is for 3 years, with the possibility to extend the position into a 4-year position by further agreement where 25% of the work will be designated to teaching and other relevant work at HVL.
The ability to start the position timely after the project start (March 1st, 2024) will be considered an advantage when candidates are ranked due to the time frame of the project, the stipulated deadlines for the project deliverables and other linked research activities.
The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to HVL.
Application procedure:
Applications will be evaluated by an expert panel 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 should be uploaded as an attachment to the online application:
Master Thesis
Copies of selected academic publications (no more than 15)
A CV with a complete list of academic publications
Diplomas and certificates
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, the applicants must submit certified translations of these. The transcripts must specify the topics, the course works, and the grades at the bachelor`s and master`s degree levels.
Applicant whose education is from another country than Norway, need to also attach a certified translation of the diploma and transcript of grades to English or a Scandinavian language, if the original is not in any of these languages. It is required that the applicant enclose a review from NOKUT whether the education (bachelor and master’s degree) is of a scope and level that corresponds to the level of a Norwegian master’s degree. Please see www.nokut.no/en for more information about NOKUT’s general recognition. This may take some time and we recommend you to apply as soon as you know you will apply for this position. If no answer within the application deadline, please enclose documentation from NOKUT that they have received your application.
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 e-mail or to individuals at the college.
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
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.
Employed on condition that you are granted a work and residence permit (must be considered individually).
Western Norway University of Applied Sciences is subjected to the regulation for export control system. The regulation will be applied in the processing of the applications.
