JOB PURPOSE: 

The post-doctoral researcher will be responsible for

• Supervising  and overseeing ongoing work on statistical bioinformatics, data science and machine learning activities related to pathogen genomics and epidemiology.
• Supporting and contributing to the capacity-building initiatives of PEO group and KWTRP.
• Supervision and mentorship of PhD students and research assistants in the research group.
• Contributing and supporting policy engagement initiatives of PEO group.
• Developing own body of work and mobilization of research funding to support transition to research independence.

REPORTING LINES

REPORTS TO: Principal Investigator

INDIRECT REPORT : Research officers and assistant research officers.

INDIRECT REPORTEES: Ph.D. students and research assistants

SUMMARY

The primary responsibility will be to coordinate and support a body of work focused on data analysis of epidemiological and genomic data using machine learning and data science methods.

KEY RESPONSIBILITIES:

• Gather, curate, and manage datasets related to genomic epidemiology. This will involve data cleaning, organizing, and ensuring data quality and integrity.
• Apply machine learning algorithms for the analysis of both epidemiological and genomic data and which includes variant calling, genome assembly, predicting functional regions and elements in viral genomes.
• Develop and apply statistical analysis techniques to identify patterns, trends, and associations with data.
• Develop computational tools, scripts, and dashboards to facilitate data analysis, visualization and interpretation using R, Julia and Python or other relevant programming languages and frameworks.
• Publish research findings in high-quality scientific journals and present at conferences and workshops to disseminate knowledge and contribute to the fields of public health, genomics and epidemiology of infectious diseases.
• Provide technical expertise and guidance to project teams and partners on best practices for integrating Statistical and bioinformatics pipelines including machine learning methods.
• Contribute to grant writing and proposal development to secure funding for research projects related to application of data sciences in genomics.
• Mentor and supervise junior researchers and students across the PEO and SECCAB projects involved in research projects, providing guidance and support in their professional development

REQUIREMENTS

QUALIFICATIONS:

• PhD in a relevant field (e.g., statistics, bioinformatics, data science, epidemiology) with a focus on statistics and machine learning.
• Strong background and demonstratable expertise in statistics including Bayesian analysis.
• Proven track record of publishing research articles in reputable scientific journals, preferably in the fields of Data Science, epidemiology, Bioinformatics, or related areas.
• Solid quantitative and strong analytical skills, including experience using statistical software (e.g. R, Python, Julia) for data analysis and interpretation.

DESIRABLE

• Excellent written and verbal communication skills, with the ability to effectively communicate complex research findings to diverse audiences.
• Ability to work effectively in multidisciplinary teams and collaborate with researchers, policymakers, and healthcare practitioners in Africa.
• Strong organizational skills, attention to detail, and ability to manage multiple tasks and deadlines.
• Willingness to travel as needed.

COMPETENCIES:

• Demonstrated high levels of confidentiality and integrity.
• Excellent interpersonal, written, presentation and communication skills.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong Management, leadership, and decision-making skills,
• Ability to build strong and diverse effective teams, delegation, and team motivation.
• Ability to build productive and collaborative relationships with varied stakeholders.