Perform computational analyses of complex genomics and other ‘-omics’ datasets (sequence alignments, FASTA, SAM/BAM and VCF files, phylogenetic trees, etc), provide synthetic and graphical representations of the results, and interpret the same
Drive post-sequencing analyses (whole-genome reconstruction at chromosome or telomere-to-telomere level) based on long reads obtained from ILRI’s Oxford Nanopore Technologies platform.
Help scientists design and run their experiments on the same platform
Make the most effective use of the computational resources on ILRI’s High Performance Cluster; participate actively in the development of in-house scripts and pipelines to be hosted on BecA’s GitHub account and other ad-hoc storage space. Use and develop Nextflow/Airflow pipelines whenever necessary
Participate in the designing, planning and delivering capacity building activities such as short training workshops, seminars, bioinformatics Communities of Practice, etc
Provide informed advice to the Head of Data & Research Methods on questions pertaining to the maintenance and development of the bioinformatics platform (on both hardware and software aspects)
Contribute to the resource mobilisation efforts, be they in human resource (e.g. recruiting external trainers for workshops) or financial resource (e.g. writing grant proposals)
Support student supervision and academic capacity-building activities, especially in the frameworks of the One CGIAR Initiatives
Perform any other related duties as may be required
Requirements
Masters degree in computer science, data science, bioinformatics, computational biology, biotechnology, biostatistics or a relevant field.
Three years relevant experience with at least some analysis work performed based on 454, Ion Proton, Illumina, Oxford Nanopore or PacBio sequencing data.
Excellent working knowledge of GNU/Linux systems such as Debian/Ubuntu or CentOS
Ability to read and write programs fluently in at least two of the following languages: Python, Bash, R, Perl
Experience with distributed computing environments with load schedulers such as SLURM, SGE or Torque
Experience with modern version-control platforms for collaborative coding such as GitHub
A good understanding of the principles of molecular biology
A good understanding of the principles of molecular evolution and the ability to perform phylogenetics/phylogeographics reconstruction
An excellent attention to detail that needs to be put constantly in use, especially regarding programming
Familiarity with bioiformatics tools for genome assembly and variant calling
Familiarity with the Oxford Nanopore technology platform will be an added advantage
Familiarity with at least one workflow management system like Nextflow, SnakeMake or Airflow
Knowledge of at least one GUI-based boinformatics suite such as CLC Genomics Workbench, UGENE, Mega, etc.
