.Principal Investigator – Computational Cancer Genomics We are seeking a highly skilled and motivated Principal Investigator with expertise in computational cancer genomics, specialising in whole genome sequencing (WGS) and the development and implementation of best practices informatic pipelines. The ideal candidate will have extensive experience in utilising cutting-edge sequencing platforms to advance our understanding of cancer biology and facilitate the translation of genomic discoveries into clinical applications. The selected candidate will Lead a dynamic research team focused on computational cancer genomics, providing scientific direction and mentoring junior staff; Design and execute experiments utilising whole genome sequencing technologies to study cancer biology, including tumour evolution, clonal dynamics, and genomic alterations; Develop and optimise bioinformatics pipelines for the analysis of WGS data, ensuring robust and reproducible results; Implement best practices for data quality control, variant calling, and annotation to identify driver mutations, structural variants, and other genomic aberrations associated with cancer; Collaborate with clinical partners to integrate genomic findings into precision medicine approaches for cancer diagnosis, prognosis, and treatment; Stay abreast of advancements in third generation sequencing platforms and emerging technologies, evaluating their potential impact on cancer genomics research; Publish research findings in high-impact peer-reviewed journals and present results at scientific conferences; Contribute to grant writing and fundraising efforts to support ongoing research projects and secure additional funding for future initiatives. Requirements Research Field: Biological sciences; Biology; Computer science; Informatics Education Level: PhD or equivalent Years of Research Experience: More than 10 English level: Excellent Skills/Qualifications Ph.D. or equivalent degree in genetics, genomics, bioinformatics, or a related field. Specific Requirements Proven track record of research excellence in computational cancer genomics (at least 7 co-authored high impact factor publications), with a focus on whole genome sequencing analysis; Expertise in bioinformatics analysis of cancer WGS data, including proficiency with programming languages (e.G. Python and R) and best practice bioinformatic pipelines including GATK, SAMtools, BWA, Manta, GRIDSS, IGV; Experience (hands-on) with third-generation sequencing platforms (e.G., PacBio, Oxford Nanopore) and familiarity with long-read sequencing data analysis techniques; Experience working withHigh-Performance Computing cluster environments (e.G
