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Associate Manager – CHM
October 17, 2017 - November 17, 2017
The Associate Manager will work with an expanding team of research, clinical and computational investigators working in cancer genomics under the auspices of the Center of Heme Malignancies, the Department of Pediatrics and the Center for Molecular Oncology at MSKCC.
We have a strong research focus on pediatric and blood cancers. In our research we plan to prospectively profile all pediatric cancers by wholegenome, as well as whole exome sequencing and RNA sequencing and study these alongside cell and patient derived xenograft models. To study the role of genetic and clonal heterogeneity in cancer we study spatially and temporally separated samples and accompany these by single cell derived experimental models. Additionally we routinely profile patients with advanced disease and no available therapeutic treatments, patients with no known drivers as well as active patients on our clinical trials.
Our mission is to establish a fully integrated research program that coordinates basic scientific discovery, early-phase clinical trials, and drug development. As part of the center’s clinical and research investigations we are generating a wealth of genomic annotation data to inform clinical decision support and develop diagnostic and disease surveillance assays informed by molecular markers. To this effect we are also developing novel methods such as deep molecular barcoding assays for monitoring minimal residual disease and or circulating tumor DNA.
The Associate Manager in Computational Biology will have a strong track record on the development, implementation and deployment of next generation sequencing pipelines. The candidate will have proven experience in the delivery of high-quality genome profiling analysis data to include wholgenome, exome and panel sequencing and RNA-sequencing. The candidate will understand well key principles of genome profiling data (sources of error, quality control, variant annotation) and will be an expert in genome annotation methods to include variant calling (substitutions, indels, structural variation, copy number alterations), assessment of purity and ploidy, reconstruction of clonal phylogenies and assessment of gene expression. As a senior computational biologist the candidate will also be responsible for the development of novel bioinformatics solutions to address the growing demands of assay development in our laboratories.
The candidate will work alongside a team of engineers and computational biologists and will directly lead an expanding team of bioinformatics data scientists. He or She will be directly involved in the experimental design of each project, data analysis, co-ordination with clinical and research collaborators and will be responsible for the production of high quality data and attainment of critical project delivery milestones.
- Capable of building strong customer relationships and delivering customer-centric solutions
- A good decision-maker, with proven success at making timely decisions that keep the organization moving forward
- Able to work effectively in an environment notable for complex, sometimes contradictory information
- Consistently achieving results, even under tough circumstances
- Adept at planning and prioritizing work to meet commitments aligned with organizational
- Adept at building partnerships and working collaboratively with others to meet shared objectives and goals
- An effective communicator, capable of determining how best to reach different audiences and executing communications based on that understanding
- Resilient in recovering from setbacks and skilled at finding detours around obstacles
- Able to operate effectively, even when things are not clear or the way forward is not obvious
- Adept at learning quickly, applying insights from past efforts to new situations
- Masters or PhD in bioinformatics – or related quantitative discipline.
- At least 5 years experience in working with wholegenome profiling data to include DNA NGS data, RNA- Seq and / or epigenetic platforms.
- Experience with development and implementation of next-generation analysis toolkits (PICARD, GATK, samtools, STAR)
- Advanced programming and analytical skills
- R or R shiny applications
- Strong track record in high-quality data generation
- Experience with parallelized computing
- IT process management, version control, and use case testing
- Prior management experience
- Work in CLIA genome analysis environments