"PhD position on AI methodology for prediction of patient outcomes using organoid models"

Are you passionate about bringing personalized medicine to the next level and make real impact in healthcare? Join our team and develop novel AI methodology to improve predictions of relevant patient outcomes based on multimodal organoid data.

Patient-derived organoids are the hallmark of personalized medicine with seemingly endless possibilities to match the right treatment to the right patient. As organoid data are often longitudinal in nature (e.g. expressed by growth curves), can be derived from various markers, and can be obtained under various experimental conditions, these data form a huge analytical challenge. Furthermore, individual predictions of relevant patient outcomes based on such complex biological data remains difficult, especially in the context of rare diseases such as cystic fibrosis. So far, there is a lack of fundamental methods research to guide in these analytical challenges.

In this PhD-project, you will propose and evaluate new AI methodology to ensure that organoid data can be used to optimally predict relevant patient outcomes. You will use a real-world case study on cystic fibrosis that allows the new methods to have direct impact.

You will be part of a multidisciplinary team of statisticians, data scientists, epidemiologists, clinicians and lab researchers, with expertise in the field of prediction modeling, longitudinal data analysis, statistics, data science, machine learning, AI, organoid models and cystic fibrosis.

The supervisory team will consist of dr. Maarten van Smeden, prof. dr. Jeffrey Beekman and dr. Danya Muilwijk.

Requirements:

• MSc in statistics, applied mathematics, computer science, AI, or a related technical discipline
• Scientific curiosity, creativity, perseverance in completing challenging projects, an interdisciplinary outlook and good communicative skills required to collaborate in a multidisciplinary team
• Demonstrable experience with scientific programming, e.g. in Python, Julia or R
• Proficiency in spoken and written English
• Desire to develop further as an independent scientist

Conditions of employment:

The maximum salary for this position (36 hours) is €3,108 gross per month based on full-time employment. In addition, we offer an annual benefit of 8.3%, holiday allowance, travel expenses and career opportunities. The terms of employment are in accordance with the Cao University Medical Centers (UMC).

The PhD candidate will be embedded in the AI methods lab of the UMC Utrecht and will work in close collaboration with laboratory experts of the cellular disease models lab and clinicians of the dept. of pediatric pulmonology of the UMC Utrecht.