Mots-Clés

Research Drug Discovery Bioinformatics Proteomics genome-wide omics MultiOmics NGS molecular screens statistical data analysis pipeline

Description

Vacancy: Senior Bioinformatician. Biology/Chemistry interface and Proteomics research

Department: Data Sciences & Quantitative Biology

Based in: Cambridge

Are you a bioinformatician passionate about biomedical research looking for an exciting and impactful new challenge? Do you have experience analysing proteome wide omics data and high-throughput molecular or genetic screens for target identification and drug discovery? Is research and development at the interface between biology and chemistry exciting for you?

Then why not join our Data Sciences & Quantitative Biology team in Cambridge, UK and apply bioinformatics and computational solutions to help us evolve and extend our capabilities in our drive to find the medicines of the future. In doing so, you will be part of a multi-disciplinary team of bioinformaticians, data scientists, image analysts and statisticians providing quantitative insights to discover new therapeutic modalities. Our group is committed to enhancing AstraZeneca’s ability to enable effective target selection and hit identification (e.g. Mervin et al, 2021 ).

This is an excellent opportunity for you to apply your bioinformatics and data analysis skills in a fast-moving and multi-disciplinary area, championing the discovery of new potential drugs for promising targets to treat disease. The role will encompass multiple approaches, including molecular bioinformatics, data integration, statistical analysis, visualisation, pipelining and close collaboration with talented chemists and biologists. As part of a global data science department, your leadership of projects will evolve at the pace of our innovative research and development of new technologies working on projects across different therapeutic areas, in close partnership with experimentalists.

At AstraZeneca, we believe in the potential of our people, and you’ll develop beyond what you thought possible. We make the most of your skills and passion by actively supporting you to see what you can achieve no matter where you start with us.

The role:

The available position is part of a team focused on protein-based and molecular bioinformatics research. Alongside your peers, you will work at the interface between biology and chemistry and impact target discovery, compound hit identification and lead optimisation.

Your main responsibilities will involve:

• Create and implement analyses and computational tools to extract value from large multidimensional datasets originating from high-throughput screens and drug discovery technologies (e.g. DNA encoded library). This could be the development of statistical and machine learning approaches to support robust hit identification and/or prediction.

• Contribute to analysing quantitative high-resolution mass spectrometry proteomics data for unbiased and targeted proteomics experiments.

• Contribute to the development of quantitative multiplexed proteomics and chemo-proteomics experiment design, analysis and interpretation.

• Contribute to MultiOmics experiments and develop data integration strategies to answer study goals. Provide mechanistic understanding where relevant through biological network analysis.

• Create robust data analyses and pipelines to inform experimental design, answer target prioritisation and drug development questions to guide decision-making.

• Understand key challenges and requirements in alignment with the work of experimental colleagues, and translate them into data analysis and solutions. Identify opportunities to contribute to projects.

• Ensure scientific excellence in analyses, software, pipelines, processes and results.

• Be efficient, practical, collaborative and proactive at delivering well-documented work.

• Proactively engage in knowledge sharing and peer support.

Minimum experience:

• PhD, postdoctoral or equivalent experience in bioinformatics, cheminformatics, computational chemistry, chemical biology, mathematics, statistics with applications to life sciences.

• Expertise in data analysis of high-dimensional datasets emerging in high-throughput screens and/or omics technologies such as (but not limited to) Mass Spectrometry, Next Generation Sequencing bulk or single cell, CRISPR screening, DNA barcoding, high-throughput cell line labelling, DNA-encoded libraries (DEL), Bead-Assisted Ligand Isolation-Mass Spectrometry (BALI-MS).

• Strong foundations in statistical analysis and modelling. Proficiency at generating and testing hypotheses on genome-scale/large-scale data using analytical and statistical methods

• Expertise in bioinformatics techniques/algorithms applied to molecular biology and therapeutics discovery (e.g. biological sequence analysis, motif discovery, sequence design …)

• Ability to work collaboratively, effectively, flexibly, and iteratively with multi-disciplinary teams (e.g. chemists, biologists, omics platform experts, data scientists, bioinformaticians, cheminformaticians or statisticians). Strong communication skills with technical and non-technical collaborators.

• Proficiency in R and/or Python for data analysis and programming

• Agile at learning new scientific and business concepts and adapting to new technologies, projects and collaborators

Desirable :

The following skills would be a plus but are not mandatory for the role:

• Experience with high-throughput drug screening technologies.

• Experience with Linux computing systems and job scheduling (e.g. slurm), with relevant programming languages and environments such as R/R-Shiny/Python/Dash/shell/perl, development tools (e.g. Git, conda), software/pipeline engineering skills, e.g. javascript and cloud-based systems (e.g. AWS), pipeline tools (e.g. snakemake, nextflow, knime) and databasing approaches (SQL and NoSQL) would be an advantage. The ability to choose the most appropriate and practical option for a given implementation challenge and timeline is critical.

• Background related to structural bioinformatics, e.g., protein structure analysis and visualisation, docking, molecular dynamics or quantum chemical calculations.

• Cheminformatics experience using tools such as RDKit or CDK to calculate similarities and cluster small molecules into families of related chemotypes.

• Understanding of cell and molecular biology, human physiology and drug discovery.