Early Post-Doctoral Researcher

JOB SUMMARY

The post-doctoral researcher will be responsible forSupervising  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.Description: REPORTING LINES:REPORTS TO:Principal InvestigatorINDIRECT REPORTResearch officers and assistant research officers.INDIRECT REPORTEES:Ph.D. students and research assistantsJOB DESCRIPTIONThe 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.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.DESIRABLEExcellent 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.

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

REQUIRED SKILLS

Reporting, Research and development, Research planning, Research publication, Quantitative methods, Data analysis

REQUIRED EDUCATION

Post-graduate education