Malawi Liverpool Wellcome Trust
Job Description
Introduction
The Malawi Liverpool Wellcome (MLW) Programme (https://www.mlw.mw) is an internationally recognised centre for research and research training, funded by the Wellcome Trust in collaboration with the Kamuzu University of Health Sciences.
This is an excellent opportunity to join one of Malawi’s leading research organizations which manages a large portfolio of research grants from international funders.
Job Summary
MLW would like to engage a skilled and dynamic individual for the position of Biostatistician. The role provides an excellent opportunity for a post holder to work and provide statistical support to the various research groups while based in the Statistical Support Unit (SSU) within the core programme. The post holder will be reporting to the head of the SSU.
The broad function of the position is to provide statistical support and training to MLW research projects, to contribute to the unit’s applied statistical research agenda and to strengthen MLW’s engagement with the wider statistical community in Malawi. The position will allow the post-holder to develop their career as a biostatistician and she / he will be supported in this professional development.
This is a Blantyre based position to be hosted at the MLW research facility for a period of one (1) year and three (3) months initially, then renewable subject to performance.
The position will attract a competitive remuneration package and training opportunities in line with our policies, compensation structure and the successful candidate’ experience.
Applicants must have a PhD degree in statistics, biostatistics or medical statistics, demonstrable working experience/knowledge in study design, data analysis and solid knowledge of statistical methods. Competency in the use of the R environment for statistical computing is essential and experience of other statistical software (e.g. Stats, SAS, SPSS) is a bonus. Experience of working with high performance computing systems is highly desirable.
Responsibilities
The Malawi Liverpool Wellcome (MLW) Programme (http://www.mlw.mw) is an internationally recognised centre for research and research training, funded by the Wellcome Trust. The post of biostatistician within the Statistical Support Unit (SSU) and the Biostatistics Associate Research Group (BARG) at MLW requires a skilled and dynamic biostatistician to provide statistical support to the various research groups at MLW and contribute to the associate group’s applied statistical research agenda. The post holder will also contribute to strengthening MLW’s engagement with the wider statistical community in Malawi. The post holder reports to the head of the SSU / BARG.
From September 2025, as MLW starts its new core grant, the current structure of SSU and BARG will change to a Modelling Unit (MU; which includes both support and research statistics) with additional statistical support run out a new integrated Clinical Trials Unit. The recruited candidate is expected to support this transition in structure.
Professional requirements:
- Provide statistical support to research groups: give advice on study design, sample size considerations, help drafting statistical analysis plans, advise on, help with or do data analysis and statistical modelling.
- Deliver short courses, workshops and tutorials on statistical design, methods and software, both at MLW and Kamuzu University of Health Sciences (KUHeS).
- Contribute to the SSU/BARG’s (and later MU) applied statistical research agenda and lead or contribute to research grant applications as principal or co-investigator or collaborator, including personal fellowships.
- Maintain high scientific standards.
- Liaise with MLW researchers, the clinical research support unit, data management staff, laboratory staff and MLW operational departments as required.
- Attend statistical trainings, workshops, short courses to continue developing as a biostatistician and making sure Good Clinical Practice and Human Subjects Protection training certificates are maintained up-to-date.
- Present work at national or international seminars, meetings and / or conferences.
- Develop academic leadership skills by among other things supervising MSc students at UNIMA or KUHEs or interns at MLW depending on the alignment of the students research and your own research interest.
- Deputize the head of the unit at institutional strategic meetings (such as monthly heads of department meetings) where necessary
- Undertake any other reasonable tasks as requested by the SSU / BARG / MU head.
Administrative requirements
- Maintain a log file recording both the projects and the time spent working on them for the purpose of invoicing recharges to projects and audit trail.
- Help with SSU / BARG / MU administrative tasks such as entering requisitions or approving purchase orders on MLW’s finance system and liaising with the facilities team at MLW when needed.
- Assist with drafting or revising standard operating procedures for the SSU.
- Assist with writing grant applications.
- Maintaining study files, documentation of all advice given and all analyses performed.
- Attend head of department or research strategy group meetings on behalf of the SSU / BARG / MU head when needed.
- Undertake any other reasonable administrative tasks as requested by the SSU / BARG / MU head.
Requirements
D(a) Education: The minimum level of education required to perform all the duties of the job to standard.
- [Essential] MSc (or equivalent) degree in statistics, biostatistics, medical statistics, epidemiology or equivalent.
- [Essential] Ph.D. (or equivalent) degree in statistics, biostatistics, medical statistics or equivalent.
D(b) Experience: The minimum number of years of experience required to perform all the duties of the job to standard.
- [Essential] At least 3 years’ experience of applying and / or researching statistical methods.
- [Essential] At least 3 years’ experience in data analysis and / or management.
- [Essential] At least 3 years’ experience with statistical software: R is essential, experience with Stata and SAS is desirable.
- [Desirable] Previous, professional experience of working with biomedical data, such as clinical trials or epidemiological studies.
- [Desirable] Experience of working in a health-related research environment.
E KEY COMPENTENCIES/ATTRIBUTES AND SKILLS (e.g. IT Skills, Personality, Communication, Teamwork etc)
- [Essential] Statistical computing skills: R (at proficient level) and, ideally, Stata or SAS (any level)
- [Essential] IT Skills: MS Word, Excel, PowerPoint (competent)
- [Essential] Scientific integrity.
- [Desirable] Scientific computing skills: Unix shell scripting, Python, Julia, HPC skills
- [Desirable] Good communication skills to explain statistical concepts to non-statisticians such as clinical researchers.
- [Desirable] Attention to detail and ability to manage complex challenges.
F DECISION MAKING: Decisions required on the job with minimum input or checking by supervisors:
- Which statistical design or analysis is appropriate to answer a specific research question.
- How to present and interpret results from a statistical analysis.
- How to prioritise different projects.
F(a) Manuals, policies, procedures or guidelines that govern decision-making:
- SSU Handbook (MLW.HB.SSU.001)
- SSU SOPs
(MLW.SOP.SSU.001, MLW.SOP.SSU.002, MLW.SOP.SSU.003)
- MLW Code of Conduct
F(b) Financial decisions required in this job (e.g. budgets, expenditures, petty cash etc)
- Recharging studies for statistical support.
- Budgeting for grant applications where listed as investigator or collaborator.
- Budgeting for statistical workshops.
- Requesting and approving running costs of the unit through MLW finance processes.
G RESPONSIBILITY:
G(a) For people (supervisory):
- Supervising MSc thesis projects for occasional MSc students attached to the unit.
- Advise MLW students and staff on statistical matters (statistical supervision).
- Line manager future SSU / BARG / MU staff.
G(b) For resources:
- Laptop and accessories (including external monitor).
- Confidential, secure storage of all study data in line with MLW data policies.
H WORK COMPLEXITY: The degree of complexity of the job i.e. how simple, standardized or complicated the work is:
- Complex; requires professionalism and application or development of sophisticated statistical design, models and analyses while delivering within project timelines; requires interactions with researchers of various seniority as well as educational and policy stakeholders.
I ACCOUNTABILITY FOR ERRORS: The impact of errors on organizational resources, customers, processes, equipment etc.
- The post holder is responsible for the accuracy and validity of all support and applied statistical research conducted.
- The post holder is responsible for acting with scientific integrity.
- The post holder needs to comply with Good Clinical Practice (GCP) and all good practices for professional statisticians as listed in the unit handbook (MLW.HB.SSU.001).
- Errors can lead to reputational damage to MLW, retraction of publications and loss of future research funding.
J WORKING CONDITIONS: Inconvenient or disagreeable aspects of the job e.g. exposure to heat, dirt, outside work, constant interruptions, hazards, uncomfortable situations etc.
J(a) Uncomfortable Conditions:
- None; post is based in a busy, vibrant research office environment.
J(b) Job Hazards:
- Occupational hazards include long exposure to computer screens and sitting at a desk. To be mitigated by complying with desk and office chair health and safety procedures.
K ORGANISATIONAL RELATIONSHIPS/CONTACTS: Local and international contacts, frequency, purpose and method etc.
MLW recognizes its responsibility in safeguarding and protecting communities, research participants and patients with whom MLW is working.
Please note that successful candidates will be requested to undergo a safeguarding check prior to appointment and at regular time points during employment.
Suitably qualified candidates should forward their applications with copies of relevant certificates, 3 traceable professional referees and a detailed CV to [email protected] not later than 30th June 2024.
Please ensure that documents are in one (1) pdf file format and to be marked, “SSU-BIOSTATISTICIAN”.
Only short-listed candidates will be acknowledged.