PhD fellowships in Biostatistics and Causal inference at the SMARTbiomed Pioneer centre
Københavns Universitet
The Department of Public Health at the University of Copenhagen offers 1-2 PhD fellowships in biostatistics with special focus on methods development for causal discovery, causal inference and causal prediction. The anticipated hiring date is 1 May, 2025, or as soon as possible thereafter. The PhD students are expected to develop and apply statistical methodology for causal inference and discovery in observational and experimental data, and will be part of the SMARTbiomed Pioneer centre https://SMARTbiomed.dk/about-SMARTbiomed.Project Description
We invite highly qualified, thorough, and motivated applicants to apply for the position. The PhD will engage in research on causal discovery and inference, and for partially identified effects. This may include the use of partially identified estimands, causal discovery in settings with partial identification, causal discovery with temporal background knowledge, and/or causal risk prediction. An understanding of basic causal inference or causal discovery is useful, as well as experience with statistical programming and R developmentPrincipal supervisor Professor Erin Gabriel, Associate Professor Michael Sachs, or Professor Claus Ekstrøm, Co-supervisor Assistant professor Anne Helby Petersen
Start: May 1st 2025
Duration: 3 years as a PhD studentJob description
Your key tasks as a PhD student at SUND are:
Key criteria for the assessment of applicants
The successful applicant for the Ph.D. scholarship will be a statistician with a strong background in mathematics and statistics i.e., a candidate degree in for example mathematics, (bio)statistics, or engineering sciences. Accordingly, we require documented skills within theoretical and applied statistics and the ability to program in R. Also, the applicant should be interested in learning to communicate research findings in teaching, conference talks, and by writing scientific papers for international journals.
It is a prerequisite for the PhD fellowship that the candidate can be and is not already enrolled as a PhD student at the faculty of Health and Medical Sciences, University of Copenhagen.Place of employment
The place of employment is at the Section of Biostatistics, Department of Public Health, CSS, University of Copenhagen. We offer creative and stimulating working conditions in dynamic and international research environment.About the Centre: The Pioneer Centre for Statistical and computational Methods for Advanced Research to Transform Biomedicine (SMARTbiomed) will support a critical mass of researchers who focus on method and software development for analysis and inference from massive human data, advancing applications in medicine. The Pioneer Centre for SMARTbiomed will leverage large-scale, multimodal biomedical data combined with focussed innovation in statistical and computational methods including machine learning to advance our understanding, treatment, and prevention of human disease.The Centre will be anchored at Aarhus University with hub sites at Copenhagen University and University of Oxford. Prof. Naomi Wray, Michael Davys Professor, Department of Psychiatry and Big Data Institute at the University of Oxford is the SMARTbiomed Director. The leadership executive team includes five co-PIs, Professor Chris Holmes, Professor of Biostatistics at the University of Oxford, Professor Cecilia Lindgren, Professor of Genomic Endocrinology & Metabolism, Big Data Institute, University of Oxford, Professor Bjarni Jóhann Vilhjálmsson, Professor of Statistical and Psychiatric Genetics, National Centre for Register-based Research, Aarhus University and Professor Erin Gabriel, Section of Biostatistics at the University of Copenhagen.SMARTbiomed is funded by the Danish National Research Foundation, the Novo Nordisk Foundation, the Lundbeck Foundation, the Carlsberg Foundation and the Villum Foundation. Funding has been secured to support a 13-year research plan. SMARTbiomed will support researchers who focus on method and software development for analysis of, and inference from, human health-related data, advancing applications in medicine. We will create a vibrant international community of researchers, both virtually and in-person, providing an exciting environment of collaboration to attract early-career researchers from a wide variety of fields, working as a team towards unified goals. Travel between the hubs is encouraged for all centre members.The core mission of SMARTbiomed is development of statistical and computational methods focussing on causal inference (theme lead: Erin Gabriel), risk prediction (theme lead: Bjarni Vilhjálmsson) and machine learning (theme lead: Chris Holmes). This broad focus is ring-fenced by questions relevant to common complex diseases/disorders (specifically cardiometabolic, brain and reproductive traits), and ring-fenced by big data types that are newly emerging for exploitation (‘omics, longitudinal – usually electronic health record or biobank – and clinical imaging data) Bridging omics and clinical big data within the Centre acknowledges a vision that translation of research advances from omics-based research will be facilitated by close integration with, and knowledge of, clinical data.
Information on the centre can be found at: https://SMARTbiomed.dk/
København
Thu, 09 Jan 2025 05:25:50 GMT
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