Research Assistant in Hierarchical Modelling of PET Blood Data

Research Assistant in Hierarchical Modelling of PET Blood Data

Research Assistant in Hierarchical Modelling of PET Blood Data

Do you want to contribute to top quality medical research?

We are seeking a skilled Research Assistant to join our team working on PET neuroimaging methodology at Karolinska Institutet in Solna. In this role, you will have the opportunity to work at the intersection of advanced statistical method development and translational neuroscience, contributing to the development of novel methods for molecular imaging. We offer an exciting position within one of Europe’s leading medical research environments. The employment is limited to a period of three months.

Your mission

You will work on modelling arterial input functions using arterial blood sampling data to improve the quantification of in vivo molecular imaging. In this role, you will contribute to bringing a new method to publication in an international scientific journal.

The work involves further development, evaluation and scientific reporting of a hierarchical nonlinear modelling framework for estimating arterial input functions in PET, together with a flexible model of residual variance using iterative reweighting. Specific tasks include:

• Refinement and evaluation of non-linear mixed-effects models of arterial blood data across multiple datasets with different radiotracers
• Modelling of heteroscedastic variance structures using hierarchical generalised additive models
• Evaluation of model robustness for missing-data scenarios, and assessment of the impact on downstream kinetic quantification
• Drafting a manuscript for submission to an international peer-reviewed journal, and documentation of the analysis code in R 

Your profile

We are looking for a candidate who is analytically rigorous and comfortable working with complex models that require both statistical judgement and programming proficiency. Given the short duration of the appointment, you should have relevant experience that enables you to quickly become familiar with the work and contribute independently to completing a scientific manuscript. You should also be able to communicate technical results clearly to an interdisciplinary audience.

Requirements 

• Master's degree in statistics, bioengineering, biomedical engineering, or a closely related quantitative discipline 
• Demonstrated proficiency in R
• Documented experience of fitting hierarchical non-linear parametric models to pharmacokinetic or other physiological time-series data
• Documented experience of accounting for heteroscedasticity using iteratively reweighted least squares (IRLS) or location-scale families
• Documented experience of non-parametric hierarchical models, such as hierarchical generalised additive models (HGAMs)
• Some knowledge and experience with blood sampling procedures
• Good written and spoken English

Meritorious

• Experience of PET quantification, particularly modelling of blood data
• Prior experience with pharmacokinetic or epidemiological compartmental models
• Experience of presenting methodological work at an international conference
• Knowledge of neuroscience and neuroimaging, for example from advanced-level coursework 

What do we offer

A creative and inspiring environment with wide-ranging expertise and interests. Karolinska Institutet is one of the world's leading medical universities. Our vision is to pursue the development of knowledge about life and to promote a better health for all. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. Karolinska Institutet is also a state university, which entitles you to several good benefits through our collective agreement. And you get to practice freely in our modern wellness facilities, where trained staff are on site.

Location: Solna

Read more about the Department of Clinical Neuroscience
Read more about the research group you will be part of

Application

KI applies individual and differentiated salary setting in accordance with our collective agreements RALS and RALS-T.

The application is to be submitted through the Varbi recruitment system.In this recruitment, you will apply with your CV without a personal letter. Instead, you will answer some questions about why you are applying for the job in the application form. 

Want to make a difference? Join us and contribute to better health for all

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