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PhD FELLOWSHIP WITHIN MACHINE LEARNING FOR PUBLIC HEALTH INSIGHTS
The Faculty of Information Technology and Electrical Engineering (http://www.ntnu.edu/ie) at the Norwegian University of Science and Technology (NTNU) has a vacancy for a 100% position as PhD fellow within Machine Learning for Personalized Healthcare at the Department of Computer Science (IDI) (http://www.ntnu.edu/idi).
The appointment is for a term of 3 years without duties. The position may be combined with 25 % duty primarily associated with education tasks (thus extending with an additional year). This is a researcher training position aimed at providing promising future researchers the opportunity of academic development in the form of a doctoral degree.
Information about the department
The Department of Computer Science currently employs 28 full time professors, 60 associate/assistant professors, 19 adjunct professors, 37 postdocs/researchers, 90 PhD students, and 22 technical/administrative staff. The department has had research and educational programs in Artificial Intelligence and Machine Learning since the early nineties.
The department’s research in machine learning contributes to the state-of-the-art of individual methods and algorithms as well as combinations of methods targeting particular tasks. For example, combining data-intensive methods with knowledge-based methods to produce user explanations for decision support. Thus far, our strongest contributions to the international research front have been within Bayesian learning and probabilistic reasoning, evolutionary learning and neural networks, and instance-based learning and case-based reasoning. In addition, we have ongoing activities at a high international level within large-scale data and information management. Over the last years there has been an increased interest in combined methods, e.g. integrating probabilistic and instance-based learning methods, or combining deep neural networks with reinforcement learning, applied to large volumes of data.
Machine Learning method for insights in public health
The PhD position will be part of a well-established research collaboration between IDI and the Department of Public Health and Nursing (ISM) (http://www.ntnu.edu/ism). The goal for the PhD position is to work on methods for analyzing heterogeneous healthcare data (sensor data, biomedical data, subjective data) and improve personalized recommendations.
We would like to develop knowledge-based methods and tools that focus on public health challenges (either on the clinician or the patient sides) and investigate how new types of data can be used to gain more insight and enable customizable recommendations.
The PhD fellow will be a member of the Data and Artificial Intelligence group and will participate in relevant research activities within the on-going collaboration. For this reason, a successful candidate is expected to perform excellent research within AI, machine learning, data analytics, case-based reasoning or related areas.
A master's degree in Computer and Information Science or equivalent with very good results is required, with an average grade B or better as measured in ECTS (European Credit Transfer System) grades, or an education at the equivalent level. A solid knowledge of machine learning or related methods is essential, and a research-oriented master thesis within one of these or related areas is expected. Good programming skills are required.
Applicants who do not master a Scandinavian language must provide evidence of good English language skills, written and spoken. The following tests can be used as such documentation: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:
• TOEFL: 600 (paper-based test), 92 (Internet-based test),
• IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted),
• CAE/CPE: grade B or A.
In extraordinary circumstances, formal documentation of language skills can be relinquished. In such cases the candidate’s language skills will be assessed in a personal interview.
Appointments are made in accordance with the regulations in force regarding terms of employment for PhD candidates issued by the Ministry of Education and Research, with relevant parts of the additional guidelines for appointment as a PhD candidate at NTNU. Applicants must undertake to participate in an organized PhD programme of study during their period of employment. The person who is appointed must comply with the conditions that apply at any time to employees in the public sector. In addition, a contract will be signed regarding the period of employment, including duty work if relevant.
Applicants must be qualified for admission as PhD students at NTNU. See http://www.ntnu.edu/ie/research for information about PhD studies at IE, NTNU. Together with the application, include a description of the research work that is planned for completion during the period of the grant.
The position is in code 1017 Stipendiat, minimum salary grade 50 in the Norwegian State salary scale, typically in salary grade 50-57, gross NOK 432,300 - 485,700 per year, depending on qualifications. A deduction of 2 % is made as a statutory contribution to the Norwegian Public Service Pension Fund.
We can offer
• an informal and friendly workplace with dedicated colleagues
• academic challenges in an international environment
• attractive schemes for housing loan, insurance and pensions in the Norwegian Public Service Pension Fund
The Faculty of Information Technology and Electrical Engineering want to attract outstanding and creative candidates who can contribute to our ongoing research activities. We believe that diversity is important to achieve a good, inclusive working environment. We encourage all qualified candidates to apply, regardless of the gender, disability or cultural background.
NTNU wants to increase the proportion of women in its scientific posts. Women are encouraged to apply. The appointment is subject to the conditions in effect at any time for employees in the public sector.
As far as possible, the State workforce should reflect the diversity of the population. Goals of our personnel policy therefore include a balanced distribution in terms of age and gender as well as recruitment of people of immigrant background.
Under Section 25 of the Freedom of Information Act, information about the applicant may be made public even if the applicant has requested not to have his or her name entered on the list of applicants.
The application requirements:
The application must contain:
• Curriculum vitae (CV) with information about the candidate’s prior training, exams, and work experience
• Certified copies of transcripts and diplomas
• Applicants from universities outside Norway are kindly requested to send a diploma supplement or a similar document, which describes in detail the study and grading system and the rights for further studies associated with the obtained degree
- A Statement of Purpose (2 pages) including
- A short presentation of the motivation for a PhD study
- How the applicant sees his/her background suitable,
- The applicant’s view of research challenges within the area of the PhD position
- How AI or machine learning methods such as data analytics, case-based reasoning or others can be advance the health care landscape,
- How the competence of the applicant can contribute to solving these challenges
- Names and contact information of at least 2 reference persons
- A copy of the master thesis (in PDF), or, for those who are near to completion of their MSc, an extended abstract combined with a statement of how and when the applicant plans to complete the thesis (1 page)
Incomplete applications will be rejected.
The application must be sent electronically as one combined PDF file via this page (jobbnorge.no). Potential successful candidates will be interviewed via Skype or other means.
For further information about the fellowship, please contact Associate Professor Kerstin Bach, e-mail: email@example.com, phone: + 47 73597410, or head of the department Professor Maria Leztizia Jaccheri, e-mail: firstname.lastname@example.org, phone: +47 73593469.
For information about processing of applications, please contact Senior Executive Officer Anne Kristin Bratseth, phone +47 73 59 67 15, e-mail: email@example.com.
Mark the application: IE 069-2017
Deadline for application: 2017-06-02
- Søknadsfrist2. juni 2017
- ArbeidsgiverNTNU - Norwegian University of Science and Technology
- Intern-IDIE 069-2017
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