|Published||October 29, 2022|
This is NTNU
NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim. At NTNU, 9,000 employees and 42,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here.
About the position
The Department of Mental Health and The Trondheim Sleep and Chronobiology Research group has a 3-year PhD position in the field of Machine learning for understanding mental health interventions.
The Norwegian Open AI Lab and Data and Artificial Intelligence group (DART) also has one 3-year (or 4-year with optional academic duties) PhD position on the same project, follow this link to apply for the position.
The two positions are listed separately but are both part of a research collaboration between the Department of Computer Science and the Department of Mental Health at NTNU and St. Olav’s hospital in Trondheim, Norway. In this collaboration we aim at conducting interdisciplinary research towards developing methods for personalized treatments. We have an open and interactive research environment with PhD Candidates, Postdoctoral Fellows and professors working together on novel concepts on how to utilize technology in societal challenges.
This PhD Candidate will work on unique mental health datasets that have been collected in previous Randomized Controlled Trials. During the project, the candidate will develop models using machine learning methods to predict and explain the responders/non-responders to treatment. The work will be conducted in an interdisciplinary team with a goal to use the resulting models supporting decisions on whether the treatment is promising. A second dataset on the monitoring of movement will be made available during the project and can be explored by the candidate.
We anticipate the starting date for the candidate to be during spring semester 2023. For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree.
Duties of the position
The PhD Candidate must have profound knowledge of modern machine learning methods, frameworks, and tools. Ideally, the candidate has a master’s thesis in this field. Moreover, the candidate needs to be open and be able to communicate technical details to non-technical collaborators.
The main duties and responsibilities for the position are:
- Develop research prototypes within collaborative, interdisciplinary research projects
- Work in close collaboration with researchers in mental health
- Test and evaluate the solution in simulated and real environments
- Disseminate results through publications and presentations
- Participate in work in the scientific group
The list is not exhaustive.
Required selection criteria
- Your education must correspond to a five-year Norwegian degree programme, where 120 credits are obtained at master's level.
- You must have a strong academic background from your previous studies and an average grade from the master's degree program, or equivalent education, which is equal to B or better compared with NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic basis. If you have a weaker grade background, you may be assessed if you can document that you are particularly suitable for a PhD education.
- You must meet the requirements for admission to the Faculty of Medicine and Health Sciences doctoral program.
- You must have good written and oral English skills.
- You must have a professionally relevant background in Artificial Intelligence.
- You must have practical experience using machine learning frameworks and excellent knowledge of Python.
The appointment is to be made in accordance with Regulations concerning the degrees of Philosophiae Doctor (PhD) and Philosodophiae Doctor (PhD) in artistic research national guidelines for appointment as PhD, post doctor and research assistant
Preferred selection criteria
- Strong background in one or more of the following areas: artificial intelligence or machine learning
- Knowledge on systematically storing and organizing large datasets and source code management (GitHub, etc.)
- Background in medicine, clinical psychology, or neuroscience
- Good written and oral Norwegian Language skills
- Ability to take initiative and work independently
- A positive and professional attitude as well as being a good team-worker
- Social adaptability and communication skills
- Willingness to learn new skillsets
Emphasis will be placed on personal and interpersonal qualities.
Salary and conditions
As a PhD candidate (code 1017) you are normally paid from gross NOK 501 200 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The period of employment is 3 years.
Appointment to a PhD position requires that you be admitted to the PhD programme at the Faculty of Medicine and Health Sciences;
PhD in Medicine and Health Science or PhD in Medical Technology within three months of employment, and that you participate in an organized PhD programme during the employment period.
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 NTNU. After the appointment you must assume that there may be changes in the area of work.
It is a prerequisite you can be present at and accessible to the institution daily.
About the application
The application and supporting documentation to be used as the basis for the assessment must be in English.
Publications and other scientific work must follow the application. Please note that your application will be considered based solely on information submitted by the application deadline. You must therefore ensure that your application clearly demonstrates how your skills and experience fulfil the criteria specified above.
The application must include:
- CV and certificates
- transcripts and diplomas for bachelor's and master's degrees. Description of the documentation required can be found here.
- A copy of your master's thesis. If you recently have submitted your master's thesis, you can attach a draft of the thesis. If you have not completed the master's degree, you must submit confirmation that the master's thesis has been submitted. Documentation of a completed master's degree must be submitted before signing a contract of employment.
- Name and contact information of three referees
- If you have publications or other relevant research work please include up to 5
- Research statement (max. 3 pages) including:
- A short presentation of their motivation for a PhD study
- How the applicant sees their background suitable for the position
- The applicant’s view of research challenges for the selected PhD position, as well as their theoretical and methodological approach to the challenges.
If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both bachelor's and master's education, in addition to other higher education. If you already have a statement from NOKUT, please attach this as well.
We will take joint work into account. If it is difficult to identify your efforts in the joint work, you must enclose a short description of your participation.
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal and interpersonal qualities. Motivation, ambitions, and potential will also count in the assessment of the candidates.
NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.
NTNU believes that inclusion and diversity is our strength. We want to recruit people with different competencies, educational backgrounds, life experiences and perspectives to contribute to solving our social responsibilities within education and research. We will facilitate for our employees’ needs.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens, and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.
As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.
A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you want to reserve yourself from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the reservation is not accepted.
If you have any questions about the position, please contact Gunnar Morken, telephone +4791853705, email email@example.com
If you have any questions about the recruitment process, please contact Senior Executive Officer HR Fiona Druett, email firstname.lastname@example.org
Please submit your application electronically via jobbnorge.no with your CV, diplomas, and certificates. Applications submitted elsewhere will not be considered. Diploma Supplement is required to attach for European Master Diplomas outside Norway. Chinese applicants are required to provide confirmation of Master Diploma from China Credentials Verification (CHSI). Upon request, you must be able to obtain certified copies of your documentation.
Application deadline: 16.11.2022