Research Assistant

Imperial College London; London; On-site; GBP 35,000 - 55,000; Full time

Job summary

Imperial College London is offering a unique opportunity for a postdoctoral researcher to contribute to an impactful project on onchocerciasis transmission dynamics. This role involves utilizing advanced modeling techniques to assess the epidemiological effects of moxidectin compared to ivermectin in Central Africa. You will be working in a supportive and collaborative environment, with ample resources for career progression, and a competitive remuneration package.

Benefits

39 days off a year

Generous pension schemes

Access to sector-leading resources

Promotional opportunities

Inclusive work culture

Qualifications

• Experience in R and Python programming.
• Familiarity with stochastic modelling.
• Solid understanding of Neglected Tropical Diseases and epidemiology.

Responsibilities

• Assist with data analysis and model refinement.
• Ensure validity of data and model outputs.
• Participate in field work related to the project.

Skills

Programming in R

Programming in Python

Stochastic modelling

Data analysis

Knowledge of epidemiology

Knowledge of Neglected Tropical Diseases

Education

First / MSc degree in Computer Science / Epidemiology

Job description

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The post is funded by the European & Developing Countries Clinical Trials Partnership (EDCTP3; Project Acronym: EMINENCE = Eliminating onchocerciasis with Moxidectin IN ENdemic hotspots of CEntral Africa) to investigate the transmission dynamics and epidemiological impact of annual or biannual moxidectin mass drug administration (MDA) compared to annual ivermectin MDA on Onchocerca volvulus transmission hotspots in the Centre Region of Cameroon.

The overall aim of the post will be achieved through the following specific objectives:

1. To use the stochastic, individual-based EPIONCHO-IBM transmission model for simulating the history of interventions in the study area and comparing to Year 1 study baseline (model calibration).
2. To generate projections of the epidemiological impact (on infection trends in humans and vectors, and anti-Ov16 seroprevalence in children) of the interventions in the Phase IIIb trial: (a) biannual moxidectin MDA; (b) annual moxidectin MDA; (c) annual ivermectin MDA, both during the duration of the trial and in the long term (model projections).
3. To model onchocerciasis-associated morbidities (at baseline and as a result of the interventions under comparison): onchocerciasis skin disease, onchocerciasis ocular disease and onchocerciasis-associated epilepsy (modelling morbidity).
4. Depending on nodulectomy data to be collected in Year 1 and Year 5, estimate macrofilaricidal (killing of adult worms) and sterilizing effects of multiple doses of moxidectin (five doses in the biannual moxidectin arm; three doses in the annual moxidectin arm) compared to annual ivermectin (modelling anti-macrofilarial effects).
5. Calculate elimination probabilities when switching to annual or biannual moxidectin compared to continuing annual ivermectin (modelling elimination).
6. Support the economic evaluation of annual or biannual moxidectin compared to ivermectin work-package (health economics).

Some of the key responsibilities are:

1. To assist with the analysis of the data to be collected during Year 1, as well as baseline data for the study area.
2. To refine the EPIONCHO-IBM model code as required (e.g., stochasticity in the microfilarial component; excess human mortality; morbidity sub-models; secular and community-based vector control transmission trends).
3. To ensure the validity and reliability of data, model code and model outputs at all times.
4. To maintain, improve and annotate model code.
5. To maintain accurate and complete records of all findings, including visualisations of model outputs.
6. To participate in fieldwork as described in the project.
7. To help strengthen relevant modelling and data analytics capacity of research partners in Cameroon.
8. A first / MSc degree (or equivalent) in Computer Science / Epidemiology.
9. Experience of programming in R, Python.
10. Experience in stochastic modelling.
11. Knowledge of Neglected Tropical Diseases in general and onchocerciasis in particular.
12. Knowledge of epidemiology and transmission dynamics of vector-borne (macroparasitic) infections.
13. Knowledge of basic research methods, data analysis and advanced statistical methods.
14. The opportunity to continue your career at a world-leading institution and be part of our mission to advance science for humanity.
15. Grow your career: gain access to Imperial’s sector-leading resources as well as opportunities for promotion and progression.
16. Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).
17. Be part of a diverse, inclusive, and collaborative work culture with various resources to support your personal and professional development.