Folkehelseinstituttet

Oslo

Heidi Aase

Avdelingsdirektør

<em>Do you excel in data science and want to apply your skills to high-impact public health research? We are seeking a data-driven researcher for a 2-year position focused on advanced statistical modelling, causal inference, and machine learning in large-scale environmental health data. This role is geared toward candidates with a strong methodological background in statistics. </em><br /><br />The position is part of the MoBa-PlastChem project, funded by the Minderoo Foundation (Australia), and seeks to investigate plastic-associated chemical exposures and endocrine disruption during pregnancy and the impact on neurodevelopmental and reproductive health outcomes in children and youth.  <br /><br />The position is located at NIPH’s Department of Child Health and Development in the Division of Public Health and Prevention. The department consists of about 20 employees, working with research projects covering a broad range of topics related to risk- and protective factors for child health and development. The department coordinates the work within NIPH’s strategic developmental plan for mental health and prevention in children and youth and has extensive collaborations with other NIPH departments and national and international researchers.  <br /><br /><strong>About the project. </strong> The researcher will be affiliated with the project “Prenatal exposure to plastic chemicals and health outcomes in children and adolescents from the Norwegian Mother, Father and Child Cohort Study (MoBa-PlastChem)”. The objective of MoBa-PlastChem is to investigate whether prenatal exposure to environmental toxicants, originating from plastic production or products, is linked to endocrine disruption and later reproductive health problems or neurodevelopmental traits/diagnoses in children and adolescents. The project uses data and biospecimen from the MoBa, as well as linkage to national health registries. This study will employ novel methods for causal inference using genetically informed approaches, alongside advanced machine learning techniques for data modelling and analysis.  <br /><br />The candidate will have the leading role in data preparation and analysis efforts in a large-scale cohort study, including the development and implementation of machine learning models, application of causal inference methods, and the integration of genotyping data to explore relationships between toxicant exposures and health outcomes, as well as steroid hormone mediation. Assessing combined effects of toxicant mixtures is also a major task, as well as leading and/or contributing to scientific publications within the project’s objectives. <br /><br />The research group consists of researchers within multiple disciplines, such as toxicology, endocrinology, analytical chemistry, epidemiology/genetic epidemiology, pediatrics, psychology, and statistics. The project groups at NIPH also collaborates with research groups in USA, UK and Australia. The candidate will work together with researchers from its own and other departments at NIPH, including The PsychGen Centre for Genetic Epidemiology and Mental Health, and Centre for Fertility and Health, in addition to national and international partners.  <br />
<h3>Work tasks</h3><ul><li>Apply and potentially develop novel statistical methods for causal interference for toxicant exposure and health outcomes, as well as steroid hormone mediation.</li><li>Responsible for management, curation and overseeing/advising all data analyses in the project </li><li>Contribute to reporting to the Minderoo Foundation (written, and in meetings) and to collaborators  </li><li>Publish or contribute to scientific articles or reports, and present findings internally and at national and international conferences/meetings   </li><li>Have an active role in internal and external collaborations   </li><li>Performe some administrative tasks may be relevant in the project   </li><li>The position may require travel to meetings and conferences </li></ul><h3>Qualifications</h3><ul><li>A PhD in biostatistics or bioinformatics is preferred. However, candidates with a strong methodological background within project relevant thematic fields, such as public health, medicine, biology, toxicology, psychology, or epidemiology, are also encouraged to apply. </li><li>Extensive experience in quantitative statistical analyses in large cohort or health registry data sets is essential.  </li><li>Proficiency in using the statistical software R is required. Competence in other coding languages (e.g. Python) is an advantage. </li><li>Experience with genotyping, other -omics data, or genome-wide association studies (GWAS) is strongly preferred. </li><li>Experience with data management and processing using Services for sensitive data (TSD) is an advantage. </li><li>Practical knowledge on working with advanced machine learning based modelling techniques and or causal inference methods is preferred </li><li>Research experience or practical knowledge in areas such as toxicant exposures and mixture analyses, neurodevelopmental outcomes, or endocrine disruption, is considered an advantage. </li><li>Proficiency in English, both written and spoken, is required. </li><li>Proficiency in Norwegian or another Scandinavian language is an advantage. Candidates not fluent in Norwegian should be willing and motivated to learn. <br /><strong></strong></li></ul><h3>Personal qualities</h3><ul><li>Strong collaboration skills in interdisciplinary teams  </li><li>Structured, flexible, efficient, and able to deliver </li><li>Ability to work independently, structured, long-term, and goal-oriented  </li><li>Contributor to an inclusive work environment   </li><li>Skilled in communication of results (oral and written)  </li><li>Personal qualities will be emphasized   </li></ul><h3>We offer</h3><ul><li>A two-year position as a post-doctoral researcher in Oslo, Norway  </li><li>The start date will be decided together with the candidate (preferably in September 2025)  </li><li>Good welfare schemes and flexible working hours  </li><li>An interesting job within an important field of research, with the possibility to develop expertise and potential for career development  </li><li>Ethical and respectful work environment  </li><li>Salary by agreement, within the state&#39;s wage regulation  </li><li>Excellent pension benefits through the Norwegian Public Service Pension Fund</li><li>Flexible working hours and attractive welfare benefits, including opportunities for exercise during working hours</li><li>Modern office facilities, with a mix of open-plan areas, smaller offices, and well-equipped meeting rooms that support collaboration</li></ul><p>The Norwegian Institute of Public Health is a unique workplace with a strong sense of social responsibility and an important role in promoting the health and well-being of the population. We are committed to building strong professional communities and emphasize the development of each individual employee, as well as their ability to influence their own workday. Here, you will work alongside dedicated and highly competent colleagues in a supportive and friendly environment.</p><p><br /></p><h3>Kontaktinformasjon</h3>Heidi Aase, Avdelingsdirektør, &#43;47 21078344<br />
<h3>Arbeidssted</h3>Marcus Thranes Gate 6<br />
0473 Oslo<br />
<h3>Nøkkelinformasjon:</h3>Arbeidsgiver: Folkehelseinstituttet FHI<br />
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Referansenr.: 4987359572<br />
Stillingsprosent: 100%<br />
Midlertidig<br />
Søknadsfrist: 10.08.2025<br />
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Researcher in Biostatistics - 2 years