PhD Studentship in AI Driven Population Health Study : Improving
medication verification for cancer patients
Dear All,
Applications are invited for a three-year PhD studentship. The studentship
will start on 1 October, 2021, or as soon as possible after that.
Project Description
Medication errors, including those in prescribing, dispensing, or
administration of a drug, are the single most preventable cause of patient
harm. They have a significant impact on the efficiency of the workflow in
pharmacy, raise safety concerns for patients, and result in a financial
burden on the healthcare systems. Within cancer treatment, emphasis on
reducing the number of medication errors has been an active research area
for many years, with understanding that interdisciplinary approaches are
vital to assure continuous improvement. Opportunities created by the
reduction of transaction times for complex computational processes and use
of machine learning to support clinical decision making, create a potential
catalyst for the development of tools for reduction in medication errors.
This PhD studentship offers an exciting opportunity of exploring AI and
machine learning with large clinical data sets residing within electronic
health records to create methods to assure the effective use of systemic
anticancer treatment (including traditional cytotoxic chemotherapy,
immunotherapy, novel oral therapies etc.) without compromising patient
safety. The studentship will require application of interdisciplinary
skills to enable cooperation between the research, clinical, industry and
patient communities in the development of a novel approach which could
enhance clinical outcomes.
Supervision Team
https://scholar.google.com/citations?user=iWiXGWMAAAAJ&hl
- Dr Edward Meinert (edward.meinert@plymouth.ac.uk)
https://scholar.google.com/citations?hl=en&user=7V-WsrwAAAAJ
- Mrs Andrea Preston (Andrea.Preston@uhbw.nhs.uk)
This PhD student will be academically advised by Professor Shang-Ming Zhou
and Dr Edward Meinert, research scientists with research interests in
applied artificial intelligence and machine learning, computing science in
health and care. The student will also be advised by Mrs Andrea Preston, a
Macmillan Divisional Lead Haematology & SW Cancer Commissioning Pharmacist.
This supervision team will assure the execution of a world-class PhD
embedded into the wider digital health ecosystem at the University of
Plymouth.
Eligibility
· This PhD studentship is offered for UK and international applicants.
· Applicants should have:
1) A first or upper second-class honours degree, and a relevant
Master’s qualification in Computing Science, Data Science, Statistics,
Health Informatics, Medical Informatics, Bioinformatics, or any areas
related;
2) Interest in working with real-world problems and large data
sets;
3) Excellent proficiency in English and outstanding
communication skills;
4) Strong analytical and programming skills;
5) A “can do”, positive attitude with an aspiration to change
the world.
· Experience in machine learning is advantageous.
· Experience in publication of peer-reviewed literature is desirable.
International Students
International applicants should meet the English language requirements,
please see the details from the University’s website
https://www.plymouth.ac.uk/international/how-to-apply/english-language-requir
ements
.
IELTS Academic 6.5 or above (or equivalent) with 5.5 in each individual
category is commonly required by the University’s Doctoral College.
How to Apply
To apply for this position, please visit:
https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/postgra
duate-research-studentships/improving-medication-verification-for-cancer-pati
ents-a-pragmatic-ai-driven-population-health-study
.
Please clearly state the name of the studentship that you are applying for
on your Personal Statement.
A research proposal is required.
Please see:
https://www.plymouth.ac.uk/student-life/your-studies/research-degrees/applica
nts-and-enquirers
for a list of supporting documents to upload with your application.
Enquiry
If you wish to discuss this project further informally, please contact
Professor Shang-Ming Zhou (shangming.zhou@plymouth.ac.uk), Dr Edward
Meinert (edward.meinert@plymouth.ac.uk), or Mrs Andrea Preston (
Andrea.Preston@uhbw.nhs.uk).
For more information on the admissions process, please contact
doctoralcollege@plymouth.ac.uk.
Closing Date
The closing date for applications is 30 July 2021. Shortlisted candidates
will be invited for interview.
Best wishes
Shangming Zhou
Shang-Ming Zhou
Professor in e-Health,
Fellow of the Higher Education Academy,
Centre for Health Technology,
Faculty of Health,
University of Plymouth,
Plymouth, PL4 8AA, UK
Email: shangming.zhou@plymouth.ac.uk ; smzhou@ieee.org
https://www.plymouth.ac.uk/staff/shang-ming-zhou
https://www.hdruk.ac.uk/people/dr-shang-ming-zhou
https://www.plymouth.ac.uk/research/centre-for-health-technology
EASST's Eurograd mailing list
Eurograd (at) lists.easst.net
Unsubscribe or edit subscription options: http://lists.easst.net/listinfo.cgi/eurograd-easst.net
Meet us via https://twitter.com/STSeasst
Report abuses of this list to Eurograd-owner@lists.easst.net
