PhD position in infectious disease modeling

The Oslo Centre for Biostatistics and Epidemiology (OCBE), Department of Biostatistics at the University of Oslo, Norway, and the Norwegian Institute of Public Health (NIPH), are seeking candidates for a PhD Fellowship within our center of excellence BigInsight.

The position is available for 3 years and is funded by BigInsight and the Norwegian Institute of Public Health. BigInsight (www.biginsight.no) is a consortium of academic, industrial and public partners, to promote research-based innovation with a yearly budget of about 4 million Euro for the period 2015-2022. BigInsight aims to be a leading international center in model-based statistics, in particular for the development of methodology related to personalized solutions and predictions of transient behaviors. The PhD student will have a 50% affiliation with OCBE at UiO and 50% with the Department of Infectious Disease Epidemiology at NIPH.

OSCE is a highly active center in biostatistics, currently including nine tenured professors and associate professors, twelve researchers, and several post-doctoral fellows and PhD students, making up a group of about 50. OCBE is internationally recognized, with interests spanning time-to-event models, data integration, causal inference, statistical genomics, Bayesian inference, informative missingness and measurement error models, epidemiological studies of lifestyle and chronic diseases, stochastic models for infectious diseases, high dimensional data and models. OCBE has numerous collaborations with leading bio-medical research groups nationally and internationally.

NIPH strives to improve health in the population through strengthening of preventive health care in the society. The institute provides evidence based guidance and advice founded on high quality research and systematic reviews of current knowledge, and holds the responsibility of ten out of the total 17 national health registries. NIPH has around 1050 employees and acts as a national competence institute for governmental authorities in the health care sector. In addition, NIPH collaborates with WHO, sister organizations and health authorities in low- and middle income countries on global health issues.

Job Description

In this project, we are interested in developing new methodology for systems of individuals which interact by forming networks, by modeling and analyzing individual-based data. One of the key applications will be the study of the spread of infectious diseases, though we will also look to other interesting applications where networks describe social interactions. Social mixing and mobility patterns are key drivers of the spatial dissemination of infectious diseases. Now, the use of mobile phone data containing geo-temporal information from individuals offers an exciting opportunity of more accurate descriptions of population movements, and hence, more accurate prediction of epidemic spread. The project will develop large-scale spatial transmission models informed by mobile phone data from Norway and Bangladesh; the mobile data are provided by Telenor, who is a partner in BigInsight. In the first project, the candidate will construct models for influenza epidemics of direct importance for national pandemic preparedness planning in Norway. The second project addresses development of models to study cholera epidemics and targeted distribution of cholera vaccines in Bangladesh. This work will be done in close collaboration with the International Center for Diarhoerral Diseases, Bangladesh and offers a unique possibility to produce results of high relevance for global health. The PhD student will be jointly supervised by researchers at NIPH, OCBE and Telenor with the aim to carry out leading edge research in network science with applications to infectious disease and personalized marketing modelling.

Qualifications/Requirements

Candidates must hold a master’s degree in statistics, mathematics, computer science or physics, or a related quantitative subject with proven excellent competence in statistics at a master level.Candidates must have full competence in programming in one or several of the languages R, matlab, C , Python or similar. Candidates are expected to be in the upper segment with respect to academic credentials.

Because network modeling is an interdisciplinary field, we seek a student with a large appetite for learning new skills and techniques and who is able and willing to exploit possibilities for innovation and creativity as they arise. We seek a highly motivated and skilled person, able to work effectively as part of a team, who is eager to both gain and share insight while being focused on publishing papers in leading international journals.

The candidate must be proficient in written and oral English, while Norwegian is not required. All PhD training at UiO can be taken in English.

Candidates without a Master's degree have time until February 15, 2016 to complete the final exam.

Personal skills

• High working capacity
• Strong dedication and motivation
• Independence skills
• Collaborative skills
• Excellent English writing and oral communication skills

The purpose of the fellowship is research training leading to the successful completion of a PhD degree. The fellowship requires admission to the research training program at the Faculty of Medicine of UiO. The admission must be approved within three months from employment at UiO as PhD student. For more information see:http://www.med.uio.no/english/research/doctoral-degree/

We offer

• Salary based on salary level 50-55(NOK 430 500-467 700) per year
• A challenging and friendly working environment
• Highly qualified supervision
• Membership in theNorwegian Public Service Pension Fund
• Attractive welfarebenefits

Evaluation of the application

In assessing applications, particular emphasis will be placed upon the academic and personal ability of the candidate to complete the project within the given time-frame and write a PhD thesis under supervision. Interviews with selected candidates will be arranged. A seminar presentation may be required. Please also refer to the regulations pertaining to the conditions of employment for research fellowship positions (English translation):http://www.admin.uio.no/admhb/reglhb/personal/tilsettingvitenskapelig/regulationstermcondition.xml

The application must include:

• Application letter, including a ½ page motivation statement and research interests
• CV (summarizing education, positions, academic work-scientific publications and other relevant activity)
• Copies of educational certificates and letters of recommendation. If the master is not yet obtained, a clear statement of plans for submission and conclusion.
• List of publications and academic work that the applicant wishes to be considered by the evaluation committee, with internet link to the documents itself. If the master thesis is not available on the web, please attach a copy.
• Names and contact details of 2-3 referees (name, relation to candidate, e-mail and telephone number)

The application with attachments is to be delivered in our electronic recruiting system EasyCruit. Foreign applicants are advised to attach an explanation of their University's grading system. Please remember thatalldocuments should be in English or a Scandinavian language.

The University of Oslo has an agreement regarding acquisition of rights to work results for all employees, with the aim to secure rights to research results, etc.

The University of Oslo has a goal of recruiting more women in academic positions. Women are encouraged to apply.

In accordance with the University of Oslo´s equal opportunities policy, we invite applications from all interested individuals regardless of sex or ethnicity.

According to the Norwegian Freedom of Information Act (offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non disclosure.

Sted: Department of Biostatistics

Contact person(s):
Birgitte Freiesleben de Blasio, tlf: 47 21076397/22851508

Online application form:[Click here]



Adresse: 0313 OSLO