A fully funded PhD studentship is available under the supervision of Dr Silvia Muñoz-Descalzo (Dept. of Biology & Biochemistry) & Dr Sofia Pascu (Dept. of Chemistry) in the University of Bath.
Develop non-invasive methods to assess optimal embryo quality using new biosensors.
According to the UK Human Fertilization and Embryology Authority, the number of couples seeking in vitro fertilization (IVF) treatments has increased every single year since 1991. These numbers are likely to increase in the first world, with an aging population which delays the age of having their first child. Moreover, while the live birth rate has increased since then (from 14% to 25% in 2012), it is still very low with 75% not being successful. The main reason for the low success rate is the poor prediction capability that clinics have in selecting high quality embryos (=those which will implant and result in a healthy baby) from those which are not.
The project involves the design and develop non-invasive optical imaging methods to assess optimal embryo quality using new biosensors, working at the interface between molecular imaging, chemical biology, synthetic biochemistry and biology. The PhD candidate will produce transition-metal based, as well as organic fluorescent nanoprobe tags which will emit in the visible range of the spectrum, as well as in the nearIR and display long-lived fluorescence lifetimes.
These probes will be tested in mouse embryos obtained from healthy young females and older females (which produce sub-optimal embryos). State of the art imaging and image analysis techniques will be used to assess nanoprobes binding.
Expertise of the supervisory team:
The PhD student will work in Dr Sofia Pascu’s lab generating the nanoprobes, where he/she will receive training and gain expertise in the areas of chemistry and molecular imaging. The work with mouse embryos and image analysis with be undertaken in Dr Silvia Muñoz-Descalzo lab, where he/she be trained in mouse embryo handling and culture, together with imaging, and image and data analysis techniques.
Informal email enquiries prior to making an application are encouraged (contact Dr Pascu at firstname.lastname@example.org or Dr Silvia Muñoz-Descalzo at email@example.com).
Applications should be made via University’s Graduate school following the link: