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PhD: mm-wave imaging for cancer detection. CDT in Metamaterials PhD

Location
Bath, NY, United States

Posted on
Feb 21, 2022

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PhD: mm-wave imaging for cancer detection. (CDT in Metamaterials, PhD in Physics)
**MEMBERS ONLY**SIGN UP NOW***.
- College Of Engineering, Mathematics and Physical Sciences
Qualification Type:
PhD
Location:
Bath
Funding for:
UK Students
Funding amount:
Tuition fees and an annual stipend allowance at Research Council rates, currently £15,609 per year for 2021-22
Hours:
Full Time
Placed On:
21st February 2022
Closes:
9th May 2022
Reference:
4369
Location:
Department of Physics and Astronomy,  Centre for Metamaterials Research and Innovation
, Streatham Campus, Devon, **MEMBERS ONLY**SIGN UP NOW***.
The **MEMBERS ONLY**SIGN UP NOW***.’s Centre for Doctoral Training in Metamaterials, with industry partners QinetiQ, is inviting applications for a fully-funded PhD studentship.  The studentship can commence in early 2022 or as soon as possible thereafter.  For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £15,609 for 3.5 years full-time, or pro rata for part-time study. 
The student would be based in the Department of Physics and Astronomy in the College of Engineering, Mathematics and Physical Sciences at the Streatham Campus in Exeter.
Project Description:
Radiation in the mm-wave band is intrinsically safe, non-ionising and non-destructive. These frequencies also correspond to a “sweet spot” in the electromagnetic spectrum, where radiation can pass unimpeded through fatty tissues that normally scatter or absorb infrared and visible radiation, while giving rise to useful contrast in protein rich tissues for cancer imaging. This contrast arises primarily from the differing water content in tissues, allowing one to effectively image the water rich tumour tissue through the normally opaque, surrounding fatty tissue. The problem with standard implementations of RF and mm-wave imaging is depth determination - how does one determine the depth of healthy tissue across the entire surface of a tumour?
In this project we will develop a new strategy to this well-known problem using frequencies in the range 10 to 50 GHz. Combining this with Exeter developed techniques for near field modulation [1-3] and super-resolution imaging [4], we will be able to image water contrast at differing depths within tissues. We will first optimise the technique, tuning the imaging depth of view to match current guidelines for breast cancer margins, before testing our imaging approach by measuring excised breast samples in the operating theatre unit at the Royal Devon and Exeter Hospital, using histopathology and deep Raman measurements for comparison at known locations. Once fully designed and optimised, we believe that this approach could reduce the occurrence of second surgeries, cancer reoccurrence and metastasis.
Applicants must have a working knowledge of optics, and have taken modules in optics and/or electromagnetism during their undergraduate degree. Proficiency in programming using Python, Matlab or Labview would also be helpful.
The Award:
This award provides annual funding to cover Home tuition fees and a tax-free stipend.The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.
This studentship is open to UK and Irish nationals, who if successful in their application will receive a full studentship including payment of university tuition fees at the home fees rate.
Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in Physics or an appropriate area of science or technology.  
Applicants must have a working knowledge of optics, and have taken modules in optics and/or electromagnetism during their undergraduate degree. Proficiency in programming using Python, Matlab or Labview would also be helpful.
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