Post-Doc Position: Mathematical Modelling to optimise IVF Outcome with a Personalised Medicine...

Post-Doc Position: Mathematical Modelling to optimise IVF Outcome with a Personalised Medicine Approach

This is an interdisciplinary Post-Doc position funded by a 3-year grant from the Personalised Health and Related Technologies (PHRT ) program. You will work in the group of Prof Iber (ETH, computational biology), and collaborate with Prof Ulbrich (ETH, animal physiology), and Prof De Geyter (University Hospital Basel, reproductive medicine). 

The preferred starting date is October 2022; the exact starting date can be negotiated.

The goal of the project is to develop computational personalized medicine approaches to improve the success rate of in vitro fertilization (IVF) using human and farm animal data. Given our detailed understanding of ovarian follicle maturation, personalized medicine approaches can go beyond statistical correlation and can be based on a mechanistic understanding of the hormonal control of ovarian follicle maturation.

You will focus on the development of predictive mathematical models that integrate literature data and newly generated data from farm animals and patients (3D images, hormone levels, gene expression time series) into a consistent framework that will allow us to provide data- and model-driven guidance regarding the best IVF treatment schedule. In collaboration with a PHRT-funded PhD student, the mathematical model will be carefully tested in clinical settings and then integrated into software for clinical use.

• an internationally highly competitive salary and further benefits
• excellent working conditions, with the possibility to work partly in the home office
• a friendly and collaborative working environment
• the opportunity to translate science to the clinic
• support for career development after the PHRT-funded Post-Doc via suitable academic fellowships such as SNF Ambizione , or an ETH Pioneer Fellowship to commercialise the results

• You are experienced in building mechanistic, predictive mathematical models based on biological data.
• It is a plus if you have previous experience with image processing, finite element methods, and software engineering, as well as expertise regarding the female endocrine and reproductive system. 
• You are self-motivated and enthusiastic about leveraging mechanistic modelling for personalised medicine, advancing FemTech, and contributing to the establishment of a strong personalised medicine/personalised health research community in Switzerland, for the eventual benefit of patients and citizens.

ETH Zurich is one of the world’s leading universities specialising in
science and technology. We are renowned for our excellent education,
cutting-edge fundamental research and direct transfer of new knowledge
into society. Over 30,000 people from more than 120 countries find our
university to be a place that promotes independent thinking and an
environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to
develop solutions for the global challenges of today and tomorrow.

We look forward to receiving your online application with the following documents:

• Letter of Motivation
• CV
• Diplomas & Transcripts
• contact details of 2 referees

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about the group can be found on our website . Questions regarding the position should be directed to Prof Iber by e-mail: [email protected] (no applications).