Location: | Nottingham |
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Salary: | £28,762 to £35,333 per annum (pro rata if applicable) depending on skills and experience (minimum £32348 with relevant PhD) |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 23rd March 2023 |
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Closes: | 4th May 2023 |
Job Ref: | SCI594622X1 |
We are seeking postdoctoral scientists to join an EPSRC funded project that will design and synthesise bio-instructive materials to manufacture translation ready medical devices.
A novel class of polymers developed in our labs show great promise in reducing infections and controlling host response in the clinic. We recently added the use of micro topography to provide a synergistic stimulus to tackle infections and found an improvement in the host immune response. This control of host response is applicable to achieving better implant integration and wound healing. These findings are being developed in this project to improve outcomes for medical devices in the clinic.
In this EPSRC funded project we will use combinatorial material libraries in ChemoTopo Chips using cutting edge 3D printing technologies. These will be employed to both discover new ‘immune-instructive’ chemistry-topography combinations and probe the mechanisms that underpin their cell-instructive ability. We will develop machine learning models across a range of surfaces which correlate polymer molecular structure, surface chemistry, topography, manufacturing fidelity and bio-interfacial composition with immune and stromal cell responses as well as bacteria biofilm resistance. These models will be used to design optimal materials and manufacturing strategies for use in implanted surgical meshes and chronic wound care products for the post antibiotic era.
The project includes computational modellers and experimentalists in the fields of polymer synthesis, 3D printing, surface chemical analysis, cellular immunology, bacteriology, proteomics and metabolomics.
The successful candidate for this post will be responsible for the surface analysis experiments and correlative data analysis with support from machine learning experts in the project in collaboration with the other 8 Post Docs. Candidates must have a PhD submitted or awarded in the area of physical or biological sciences. Experience with surface chemical analysis data acquisition and interpretation is also essential.
This post is available on a fixed term basis until 28/02/2027. Hours of work are full time (36.25 hours). Job share arrangements may be considered.
There are links to US collaborators to whom the role holder will travel, including Bob Latour (Clemson University) and Daniel Anderson and Robert Langer (MIT) and Jan deBoer in TU Eindhoven and Dave Winkler in at La Trobe University (Melbourne).
This is a collaborative project between the Schools of Pharmacy, Computer Science, Physics and Astronomy, Life Sciences and the Faculty of Engineering.
Informal enquiries may be addressed to Morgan Alexander (email: morgan.alexander@nottingham.ac.uk). Please note that applications sent directly to this email address will not be accepted.
We pride ourselves on the collegial and supportive culture created by our staff for our staff and students. We are dedicated to providing an environment which enables our staff to thrive and achieve their potential. Our commitment to Equality and Diversity has been recognised in the awards of Athena Swan Awards to the schools and faculties involved.
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Our University is a supportive, inclusive, caring and positive community. We warmly welcome those of different cultures, ethnicities and beliefs – indeed this very diversity is vital to our success, it is fundamental to our values and enriches life on campus. We welcome applications from UK, Europe and from across the globe. For more information on the support we offer our international colleagues, see our Moving to Nottingham pages.
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