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Senior Lecturer/Lecturer in Analytic Epidemiology/Data Science/Statistics

Liverpool School of Tropical Medicine (LSTM) - Kenya

Research, Teaching & Training

Education KSh Confidential
2 months ago

Job Summary

PhD or equivalent in related research area (e.g. biostatistics, medical statistics, analytical epidemiology, data science).

  • Minimum Qualification: PHD
  • Experience Level: Senior level
  • Experience Length: 5 years

Job Description/Requirements

Clinical Sciences

The Department of Clinical Sciences is seeking a Lecturer/Senior Lecturer with expertise in analytic epidemiology, data science, and/or statistics to develop and apply statistical methods to clinical trials and observational studies of malaria and other childhood diseases.


This role will work in the Malaria and Child Health research group at the Liverpool School of Tropical Medicine and partners in Malawi and Kenya. Applications from individuals with expertise in individual and cluster randomised trial design, cognitive/educational research, and/or malaria studies are particularly welcome.


You will contribute to the design and analysis of ongoing and future multi-disciplinary studies of malaria and other childhood diseases, particularly focused on school-age children. The post will involve statistical/epidemiological research, data management and visualization, statistical support and mentoring, and scientific presentation/manuscript writing. You will also be expected to bring/develop your own areas of research interest.


You will have excellent research skills, analytic expertise, and communication skills, plus the ability to work as a member of a multi-disciplinary team. The post will involve working in collaboration with and travel to LSTM research collaborations abroad, particularly in Malawi, Kenya and other parts of sub-Saharan Africa. You will also have access to supportive community in the LSTM virtual Statistics core and the Global Health Trials Unit (GHTU).


The key responsibilities of the role are:


Statistical Analysis: Conduct analysis of epidemiological, cognitive, and educational data. Prepare results for presentation and publication, contribute to writing of grant proposals and the writing of manuscripts for submission to high impact journals.

Statistical Support: Lead, advise, and assist research teams, partners, and trainees on study design and analytic approaches; Support development of data collection tools to facilitate improved data quality and statistical analysis.

Data Management and Visualization: Oversee and support data management of large studies, develop data visualizations for complex and large dataset, contribute to knowledge transfer and skill development in partner institutions.

Enhance Analytical Components: Engage with external stakeholders and partners to communicate methods, approaches and findings whilst participating in regional, national, and international level collaborations and meetings. Contribute to the capacity development in biostatistics, epidemiology, or statistical programming of partners, and to the supervision of PhD and/or Master’s project students.

General: To contribute to LSTM research with an emphasis on the development and practice of statistical and epidemiological expertise to biomedical research projects, to keep up to date with major developments in approaches or methods to malaria trials and adhere to GCP data protection regulations and ethical standards.

The ideal candidate will have well-developed applied research and analytic skills in addition to excellent communication skills – both written and verbal. Analytical, time management and organisational skills are paramount to the role. Experience in malaria research is preferred though in-depth knowledge and experience with other childhood communicable diseases is sufficient. The ideal candidate will demonstrate:


PhD or equivalent in related research area (e.g. biostatistics, medical statistics, analytical epidemiology, data science).

Experience with statistics and epidemiology in applied research.

Knowledge of biostatistics related to malaria and knowledge of malaria.

Experience with analysis of cognitive and/or education data.

Statistical programming expertise in STATA or SAS and strong preference for experience with R.

Ability to work independently and as a team player in a multi-disciplinary environment.

Experience mentoring Master’s and/or PhD candidates.

Ability to travel overseas.

(For a full list of essential and desirable criteria please refer to the job description and person specification)


Application Process: To apply for the position please follow the apply link and upload your CV and covering letter.


Due to the volume of applications, we receive, we may 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 note that the successful candidate will be required to undergo an enhanced DBS and/or other international criminal record check prior to appointment and at regular points during employment. The outcome must be satisfactory to LSTM, as the duties of this post will involve direct and/or indirect contact with vulnerable adults and/or children.


Inclusion is critical to our values at LSTM


We seek to attract and recruit people who reflect the diversity across our communities, regardless of sexual orientation, gender identity, ethnicity, nationality, faith or belief, social background, age and disability. LSTM selects candidates based on skills, qualifications, and experience. 


We welcome conversations about flexible working; and applications from those returning to employment after a break from their careers. 


About LSTM 


Founded in 1898 and the oldest of its kind in the world, the Liverpool School of Tropical Medicine (LSTM) is an internationally recognised centre of excellence for teaching and research in tropical diseases.  Through the creation of effective links with governments, NGOs, private organisations and global institutions and by responding to the health needs of communities, LSTM aims to promote improved health, particularly for people of the less developed/resource poorest countries in the tropics and sub-tropics. 

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