General Summary

The Bioinformatics Research Officer will provide advanced technical and analytical support for the computational components of the Combating Antimalarial Resistance: An AI-Driven Approach to Identify and Prioritize Key Parasite Mutations (AIMaR) project.

This position is ideally suited for a candidate who possesses strong bioinformatics skills combined with deep knowledge of malaria biology and Plasmodium falciparum. The successful candidate will leverage computational approaches to address critical malaria research questions, particularly those related to antimalarial drug resistance and immune evasion mechanisms. This role involves implementing bioinformatics pipelines, conducting genomic analyses, supporting AI model implementation, and managing computational workflows on HPC systems. The position offers substantial opportunity for skill development, co-authorship on publications, and hands-on experience with advanced computational methods including EVE and AlphaFold 3.

Key Responsibilities

• Implement and execute standardized pipelines for preprocessing P. falciparum genomic data
• Conduct quality control of raw sequence data using FastQC, Trimmomatic, and related tools
• Perform sequence alignment using BWA-MEM and variant calling using established protocols
• Apply filtering criteria to ensure high-quality variant datasets (depth, quality scores, mapping quality)
• Harmonize metadata across multiple datasets, including clinical and epidemiological variables
• Conduct GWAS analysis
• Generate comprehensive QC reports documenting data processing steps and outcomes
• Support validation of EVE predictions against experimentally confirmed variations, interpreting results in the context of parasite biology
• Troubleshoot pipeline failures and optimize computational workflows for efficiency
• Maintain version control and documentation for all analysis scripts
• Apply understanding of P. falciparum biology to inform quality control decisions and identify biologically relevant variants
• Participate in regular project meetings and present analytical findings with clear connections to malaria biology
• Collaborate with structural biologists and laboratory scientists, bridging computational and wet-lab perspectives
• Contribute to manuscript preparation, including methods sections, results interpretation, and supplementary materials
• Assist in preparing figures and tables for publications and presentations
• Support training activities for junior staff and research assistants
• Document technical procedures that will be included in the project report.
• Translate complex bioinformatics results into insights accessible to malaria researchers and public health practitioners

Academic Qualifications

• Masters in Bioinformatics
• Masters in Computational Biology

Person Specification

Qualifications:

• Master's degree in Bioinformatics, Computational Biology, Genomics, or a related field
• Strong academic record with demonstrated research productivity in malaria-related bioinformatics

Essential Technical Skills and Experience:

• Advanced proficiency in Linux/Unix, Python and/or R for bioinformatics analysis
• Solid experience with genomic data analysis pipelines (sequence alignment, variant calling, quality control)
• Experience with HPC systems, job schedulers (SLURM, PBS), and parallel computing
• Deep understanding of Plasmodium falciparum biology, life cycle, and pathogenesis
• Knowledge of antimalarial drug resistance mechanisms and molecular markers
• Knowledge of immune evasion mechanisms in P. falciparum

Personal Attributes:

• Strong analytical and problem-solving abilities with biological insight
• High attention to detail and commitment to data quality
• Self-motivated with ability to work independently
• Excellent organizational and time management skills
• Good written and oral communication skills, with ability to explain computational results to malaria biologists
• Collaborative team player who values multidisciplinary perspectives and can bridge computational and biological domains
• Adaptability and willingness to learn new methods and tools
• Integrity and adherence to research ethics and data security practices

• Implement and execute standardized pipelines for preprocessing P. falciparum genomic data
• Conduct quality control of raw sequence data using FastQC, Trimmomatic, and related tools
• Perform sequence alignment using BWA-MEM and variant calling using established protocols
• Apply filtering criteria to ensure high-quality variant datasets (depth, quality scores, mapping quality)
• Harmonize metadata across multiple datasets, including clinical and epidemiological variables
• Conduct GWAS analysis
• Generate comprehensive QC reports documenting data processing steps and outcomes
• Support validation of EVE predictions against experimentally confirmed variations, interpreting results in the context of parasite biology
• Troubleshoot pipeline failures and optimize computational workflows for efficiency
• Maintain version control and documentation for all analysis scripts
• Apply understanding of P. falciparum biology to inform quality control decisions and identify biologically relevant variants
• Participate in regular project meetings and present analytical findings with clear connections to malaria biology
• Collaborate with structural biologists and laboratory scientists, bridging computational and wet-lab perspectives
• Contribute to manuscript preparation, including methods sections, results interpretation, and supplementary materials
• Assist in preparing figures and tables for publications and presentations
• Support training activities for junior staff and research assistants
• Document technical procedures that will be included in the project report.
• Translate complex bioinformatics results into insights accessible to malaria researchers and public health practitioners

• Advanced proficiency in Linux/Unix, Python and/or R for bioinformatics analysis
• Solid experience with genomic data analysis pipelines (sequence alignment, variant calling, quality control)
• Experience with HPC systems, job schedulers (SLURM, PBS), and parallel computing
• Deep understanding of Plasmodium falciparum biology, life cycle, and pathogenesis
• Knowledge of antimalarial drug resistance mechanisms and molecular markers
• Knowledge of immune evasion mechanisms in P. falciparum
• Strong analytical and problem-solving abilities with biological insight
• High attention to detail and commitment to data quality
• Self-motivated with ability to work independently
• Excellent organizational and time management skills
• Good written and oral communication skills, with ability to explain computational results to malaria biologists
• Collaborative team player who values multidisciplinary perspectives and can bridge computational and biological domains
• Adaptability and willingness to learn new methods and tools
• Integrity and adherence to research ethics and data security practices

• Master's degree in Bioinformatics, Computational Biology, Genomics, or a related field
• Strong academic record with demonstrated research productivity in malaria-related bioinformatics