Sr. Bioinformatician - Jonsson Cancer Center

Description Thenewly formed Cancer Data Sciences group at the UCLA David Geffen School ofMedicine and UCLA Jonsson Cancer Centre is seeking a Senior Bioinformaticianwith pipeline and data science experience. The successful candidate may be asenior analyst, or a junior one ready to take the next step in theircareer. You will be working with a broad team of quantitative analysts, includingStatisticians, Data Scientists, Clinical and Basic trainees, and otherbioinformaticians. You will drive the development and application of newquantitative strategies to improve our understanding and ability to treatcancer, working with cutting edge molecular and imaging datasets. You willbe passionate about generating high-quality results, with a careful approachthat identifies potential confounders and sources of bias, andtrack-record of reproducible analyses and pipeline-development. You will applythese skills to molecular, cellular or radiologic data-analysis to uncovergeneral principles of cancer, and use these with statistical and ML methods tocreate clinically useful biomarkers. This will entail working with others,including Junior Bioinformaticians, to develop, extend and applycomputational pipelines to patient cohorts ranging from tens ofindividuals to hundreds of thousands. These will be excuted at scale viadistributed software solutions on both local HPC and cloud-based assets.Our datasets comprise petabytes, and are growing rapidly, linked tokey clinical endpoints. This requires a strong background in biology tohelp ensure the right questions are asked, but linked to strong technicaland personal communication skills, to help ensure insights are broadly adoptedand appropriate analyses are performed. In this role, you will be helping usperform research that will transform the lives of cancer patients.
Yourresponsibilities will be to use your biological and data science skills toanalyze large datasets, including identification of key features usingestablished or new pipelines, statistical and machine-learning analyses, datavisualization, and written & oral reporting to translational,biologic, translational and clinical teams. Your work may focus on a singletumour type, or may cover a broad range, focusing on a subset of datatypes. You will work with both molecular (WGS, panel-sequencing, RNA-Seq,proteomic) and imaging (digital pathology, radiomic) data, and practicalexperience in one of these two areas is essential. You will typically have twoto three major and several minor projects at any point in time. We are ina rapid growth-phase, and the successful candidate will be involvedin hiring of new team members, and supporting their training andon-boarding. Beyond your strong inter-personal skills and computer sciencebackground, you will have experience with implementation skills at least two ofR, Perl or Python. You will be comfortable in UNIX/Linux environments andproducing well-documented code. A core background in statistics is key, andsupplementation with advanced understanding of time-to-event analyses,Bayesian statistics or machine-learning is beneficial. Experience withcloudcomputing or HPC is required.
Salary range: $80100.00-$158500.00 Annual

Qualifications * Working knowledge of R, Perl or Python programming.
* Understanding of molecular biology.
* Strong verbal, interpersonal, and written communication skills.
* Basic univariate and probabilistic statistical understanding.
* Knowledge of LINUX/Unix operating system, and source-code versioningsystems.
* Applied experience with NGS, proteomics or radiomic data (>1 year).
* Master's Degree in Computational Biology, Computer Science, Biostatistics ora related
discipline.* Four years' biological and data science experience.
Preferred
* Experience with applied machine-learning (e.g. hyperparameter optimization).
* Working knowledge of containerization (e.g. Docker, Singularity).
* Data Visualization experience.
* Computer science knowledge, including software design patterns.
* Knowledge of relational database software (e.g. Oracle, Postgres).
* PhD Training in Computational Biology, Computer Science, Biostatistics or arelated discipline.