We are seeking a Scientist to join our computational biology group in the Center for Single Cell Studies (CSCS) within the Genomics team of Early Oncology Translation Medicine at AstraZeneca. This position is located in Barcelona, Spain and the scientist will be affiliated with the CSCS, based in the Greater Boston Area of Massachusetts, USA. The CSCS is building an international network of scientists passionate about leveraging cutting edge single-cell genomics technologies to develop the next generation of diagnostics, therapeutics, and treatment strategies that will improve the lives of cancer patients. The computational biology scientist will support translational research by analyzing single-cell sequencing data (e.g. RNA-Seq, ATAC-Seq, CITE-Seq) and spatial omics data for clinical trials and technology development. Biological subject matter will encompass many areas of focus in Oncology, including tumors drivers, drug resistance, immuno-oncology, and epigenetics. The ideal candidate will be a highly collaborative, team player with a strong interest in technology and cancer biology.
Responsibilities
Perform bioinformatics analyses of single-cell RNA-Seq data generated from clinical and pre-clinical samples.
Perform multi-modal (multi-omic) genomics analyses that require the integration of multiple types of single-cell genomics and spatial omics data or the integration of single-cell and bulk genomics data.
Work closely with the CSCS lab team to evaluate internally-generated single-cell genomics data.
Support the design of novel experimental strategies for single-cell genomics data generation from a variety of clinical sample types.
Develop analytical methods and pipelines for routine internal usage and evaluate publicly-available analytical tools.
Routinely share results with a diverse group of molecular & cell biologists, bioinformaticians, and clinical leads.
Qualifications
Relevant MS or BS (minimum of 2 years of experience):
Background in bioinformatics, computational biology, systems biology, biostatistics, data science or related discipline.
Technical expertise with handling next generation sequencing (NGS) data with an emphasis on transcriptomic analyses. Direct experience with single-cell RNA-Seq (scRNA-Seq) or spatial transcriptomics data is a plus. Experience with multi-modal data analyses (e.g. RNA-Seq and ATAC-Seq) is also a plus.
Working experience leveraging genomic data to study cell biology. Direct experience with cancer-focused genomic analyses is a plus.
Fluency with R and/or Python programming.
Experience with Unix and shell scripting, code documentation and version control.
Experience with high-performance computing (HPC) and HPC schedulers is a plus.
Deep understanding of cancer cell and molecular biology required. Understanding of immunology is a plus.
Deep understanding of genomics and NGS data generation required.
Skilled at sharing analyses of complex data types to non-experts. Experience with producing analytical reports for distribution to non-programmers.
Experience working in a cross-disciplinary scientific environment that requires extensive interaction with lab scientists. Prior experience directly performing cell or molecular biology lab work is a plus.
Excellent organizational skills and capacity to lead multiple projects required.
Ability to efficiently alternate between independent work and team-based science, requiring direct support of other team members.
Enthusiasm to explore new technologies and apply sophisticated analytical methods to solve complex biological problems.
Desirable Qualifications
Experience performing single-cell RNA-Seq or spatial transcriptomics data analysis in an industry setting is a plus.
Advanced background in machine learning, artificial-intelligence, Bayesian statistics or other non-traditional approaches to biological data analysis is a plus.
Demonstrated track record of performance involving the successful completion of projects. Publications in peer-reviewed journals, conference presentations, and public code repositories are a plus.
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
