PhD student in Epidemiology and Biostatistics at UMC Utretch

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PhD student in Epidemiology and Biostatistics at UMC Utretch

We are looking for someone who has (nearly) finished a master of science program (MSc) in which statistics, mathematics, or computer science play a prominent role. Experience with programming and data analysis techniques is an advantage, as well as experience with statistical software such as R, S-Plus, Mathematica or WinBUGS. Good communication skills are required, as well as in interest in methodological research within the field of clinical epidemiology and health economics.

Your position
The research section Theoretical Epidemiology and Biostatistics conducts studies aiming to improve existing and to develop new methods for design and analysis of (clinical) epidemiological studies. The section focuses on the following themes: Developing innovative designs for diagnostic and prognostic (prediction) research, Developing innovative methods for quantifying the true or added value of (new) diagnostic and prognostic tests in a multivariable clinical context, Developing innovative methods for the validation and updating of so-called clinical prediction rules, Testing and improving sophisticated methods for dealing with missing values in epidemiologic research, Investigating innovative methods for meta-analysis and individual patient data-analysis of etiologic and therapeutic studies, Development of models to combine data from randomised and observational studies including genetic information, for estimating (long term) prognosis according to specific patient characteristics in addition to treatment effects.

The research group Medical Technology Assessment conducts studies on the cost-effectiveness of new medical interventions, such as newly developed drugs, new surgical procedures or new screening strategies. Some of the focus areas of this group are: The cost-effectiveness analysis of blood safety measure, Cost-effectiveness of interventions to improve circulatory health, Development of new methods to support model-based cost-effectiveness analyses, Cost-effectiveness analysis of population screening strategies In both groups, the mentioned methodological themes are not only studied on a purely theoretical level, but are also illustrated by using empirical data from various medical disciplines. In collaboration these groups will start a new project on the development of methods to assess the actual added value of implementing new diagnostic tests. Visit Official Website.

The Theoretical Epidemiology and Biostatistics and Medical Technology Assessment groups will collaborate within a new project on the development of methods to assess the actual added value of implementing new diagnostic tests. Clinical prediction rules aim to provide a probability of the presence of a disease (diagnosis) or occurrence of a disease (prognosis) in an individual. The development of such prediction models is becoming increasingly popular, and newly developed diagnostic tests, such as biomarkers, may lead to improved prediction models. However, the evaluation of those prediction models is typically limited to an assessment of their predictive accuracy. As a result, the effects of applying new, or updated, prediction models on actual patient outcomes remain unknown. Within the field of health economics modeling methods have been developed to assess the balance between costs and effects (patient outcomes) for medical interventions. In this project we aim to use and extend these methods for the assessment of the added value of new diagnostic tests. In addition, we aim to develop methods that are able to quantify the effects of replacing an existing prediction model that is used in clinical practice with a new, or updated, prediction model. A new model may provide different risk estimates for patients, for example for cardiovascular disease, compared with the old model.

As a result the preferred treatment option may also change for specific patient subgroups, and methods need to be developed to identify these subgroups. We will use statistical methods and simulation models as well as empirical data on the diagnosis deep vein thrombosis, the prognosis of cardiovascular outcomes, and the prognosis of traumatic brain injury. In collaboration with epidemiologists, statisticians and health economists you will investigate methods to assess diagnostic tests in general and clinical prediction rules in particular. Results will be described in scientific papers, and published in international, peer-reviewed journals. Based on the papers you will write a thesis, at the end of the project. For this project a 3-year temporary position is available, starting with a 1-year contract, followed by a 2-year contract when progress is satisfactory. During the project there is an opportunity to do a master of science program in clinical epidemiology. Visit Official Website.

The maximum monthly salary for this 100% position is €2673.00 gross on the basis of full-time employment (working week of 36 hours). This is a temporary appointment for 3 jaar.

We are looking for a full-time PhD-candidate. Employment is temporary for a period of 3 years, with an initial contract for one year, and an extension of 2 years if successful. The project will be conducted in Utrecht, The Netherlands. In accordance with the university regulations for academic personnel, the gross salary will be € 2086,– in the first year to € 2550,– in the third year (fulltime).

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