Post-Doctoral Research Associate (90387)
Vector Biology
Salary: £39,906 - £43,482
Contract: Full-Time, Fixed-term appointment for 2 years
Location: Liverpool
About the role:
The Liverpool School of Tropical Medicine (LSTM) is seeking to appoint a Post-Doctoral Research Associate to join an internationally recognised team tackling a pressing public health challenge - malaria control in Sub-Saharan Africa and developing ways to do this while reducing environmental impacts.
The successful candidate will work closely with our team in Burkina Faso, and engage with manufacturers and international procurement, regulatory and guidance organisations making soft skills a critical asset. This position also offers an exciting opportunity to statistically interrogate empirical entomological and epidemiological data alongside campaign costs and to develop modes of action within the malariasimulation model - a well-established, individual-based model for malaria transmission.
While manufacturers may have already adopted efficient pathways for production in efforts to eliminate costs and align with EU regulation, there may be efficiencies to gain elsewhere in the cradle-to-grave pathway that may be applicable across products with matching delivery routes and use habits. We can identify these. Using statistical inference and transmission modelling, we can explore strategic solutions; for instance, increasing ITN use across communities can be costly as it requires focused educational efforts, however the environmental benefit could be considerable as it negates the need to ship more products, maximising efficacy from the products already available. This may shift efforts from surplus ITN circulation to localised training, benefiting human health, supporting local leadership and employment, while lowering emissions. We can establish a database of these types of information and begin building a framework for assessment through this role.
Key responsibilities will include:
Engage with national programmes, manufacturers and procurement teams to co-design and use emission models to generate auditable-quality greenhouse gas emissions data
-
Establish productive relationships with key manufacturers of ITNs to facilitate emissions estimates being developed in a standardised fashion.
-
Establish and maintain crucial relationships with National Programmes to support the communication of our work - translate science into action.
-
Collaborate with project partners across policy, industry and research to co-develop frameworks for comparison of data.
-
Communicate to these different audiences and procurement teams the knowledge generated.
Generate new data resources through published and grey literature review
-
To review the regulatory landscape identifying key resources tracking risk from insecticidal compounds to non-target organisms or ecosystems, any environmental assessments performed and waste generation knowledge
-
Develop descriptive statistical outputs to demonstrate the variation in such metrics spatiotemporally.
Apply the malariasimulation malaria transmission model to health facility data
- Demonstrate competence with transmission modelling to simulate ITNs and other interventions that are used in Burkina Faso
-
Understand current mechanisms employed by malariasimulation to capture lost efficacy with increasing phenotypic resistance
-
Simulate village-level health facility data to estimate efficacy and cost-effectiveness
Provide support and supervision to PhD students and technical staff within the group
-
Contribute to training materials for, and provide training in, analytical techniques to others in the group
-
Assist in the design and supervision of student projects
Develop novel projects
-
Generate ideas and data to support new project applications
-
Contribute to the writing of research grants/ fellowships in collaboration with PIs
-
Disseminate findings through publications and conferences, as relevant to research
The ideal candidate:
Candidates must hold a PhD in Ecology, Statistics or Mathematical modelling or a related field and must be numerate with skills in R programming and statistical analysis. Experience working cross-disciplinary, within and outside of academia and business is welcome.
What we're looking for:
-
Hold a PhD in Ecology, mosquito biology/entomology, modelling or statistics - demonstrating competent quantitative ability
-
Demonstrate experience of working between science and policy and bring the communication and diplomatic skills necessary to ensure productive and trusted working relationships are established and long-lasting.
-
Have significant experience in statistical analysis
-
Demonstrate experience in transmission modelling
-
Have experience in economic analysis or costs analysis or similar health related applications
-
Hold well-developed research skills with the ability to present research findings in oral or written format to different audiences
-
Have a reasonable publication record relevant to their stage of career
(For a full list of essential and desirable criteria please refer to the job description and person specification)
Additional benefits of joining LSTM:
-
Access to support for your career growth through a variety of internal and external learning and development opportunities
-
Employee Assistance Platform offering a range of wellbeing initiatives and support, in addition to high-street discount offers
-
30 days annual leave, plus 8 UK bank holidays, in addition to 6 Christmas closure days
-
Generous occupational pension schemes including USS (Universities Superannuation Scheme) and NHS pension schemes (subject to eligibility)
-
Government backed “cycle to work” scheme
-
Affiliated, discounted staff membership to the University of Liverpool Sports Centre
-
A range of enhanced family friendly policies
Application Process: To apply for this position please follow the apply link and upload your CV, complete our application form and attach a covering letter outlining your interest in the post, and how your skills and experience align.
Due to the volume of applications we receive, we may sometimes close our vacancies early. It is therefore advisable to apply as early as possible if you would like to be considered for a role.
Please click here to learn important information about applying for a position at LSTM.
