Geospatial Data Clerk 1 at icipe - African Insect Science for Food and Health

Overall purpose of the job

The position holder will be responsible for collecting and collating data (occurrence, bionomic, and insecticide resistance) from various sources (e.g., Global Biodiversity Information Facility (GBIF), VectorBase, MalariaGEN, Global Vector Hub) into the Vector Atlas data-hub. He/She will transform the data to the Common Data Model (CDM) for downstream analyses and will be responsible for developing/adopting bioinformatic pipelines for analysis of genomic and insecticide resistance (IR) data.

Specific Duties

The successful candidate will be expected to:

• Abstract, collate and accurately record georeferenced data (occurrence, bionomic, and insecticide resistance) from various sources (e.g., Global Biodiversity Information Facility (GBIF), VectorBase, MalariaGEN, and Global Vector Hub).
• Source malaria vector data (genomic and bionomic) from published literature.
• Continuously populate the vector atlas data platform.
• Apply the Common Data Model (CDM) for data integration across platforms.
• Conduct basic bioinformatic analysis of raw sequence data to identify molecular markers associated with insecticide resistance in malaria vectors.
• Assist in conducting training to various stakeholders including icipe postgraduate students on data documentation.

Requirements/Qualifications

• Bachelor of Science in Computer Science, Mathematics, Statistics, Bioinformatics, Population Biology
• or related field. The degree should have been obtained from a recognised university in the last three years (2019 – 2022).
• Knowledge of programming languages (e.g., R, C++, Python, and PERL).
• At least 1 year of work experience in a relevant field.
• Experience in genomics, population genetics, data manipulation, and computational biology.
• Previous experience at an international/ regional research organisation is an added advantage.
• Knowledge of commonly used tools for variant detection (samtools, bowtie2, BWA, IGV, ANNOVAR, and GATK) and file formats (BED, VCF, FASTQ, BAM, and FASTA).
• Knowledge of commonly used and publicly available bioinformatics databases (e.g. GenBank, Uniprot, DDBJ, Ensemble, GEO, SRA, ExAC, ESP,ClinVar, VectorBase, KEGG, HGMD, OMIM, PubMed, and UCSC).

Closing date: 31 May 2022