We are seeking a COMPUTATIONAL STAFF SCIENTIST who will join the teams of Dr. Mariella Filbin in the Department of Pediatric Oncology at the Dana-Farber Cancer Institute. Our goal is to develop new therapeutic approaches for children brain tumors by overcoming differentiation blocks in cancer cells. Specifically our research focuses on understanding the genetic and epigenetic changes that lock cancer cells in a stem-like state preventing differentiation into normal cells.

The successful candidate will collaborate closely with other scientists across the Dana-Farber Cancer Institute and the Broad Institute of MIT and Harvard.

Located in Boston and the surrounding communities Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer HIV/AIDS and related diseases. We strive to create an inclusive diverse and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment we educate tomorrow's physician/researchers and we work with amazing partners including other Harvard Medical School-affiliated hospitals.

• Assess and integrate new methods and algorithms for single cell multi-omics sequencing data processing and analysis

• Evaluate other experimental data generated in our labs (e.g. CRISPR screens drug synergy experiments) by adapting existing pipelines and algorithms
• Characterize chromatin states and transcriptional states of cells during normal development and oncogenesis for example from RNAseq ATACseq and ChIPseq data
• Summarize and report data and analytical methods in oral and written format

• Ph.D. Computer Science Computational Biology Bioinformatics or related disciplines

• Programming experience with at least one high-performance statistical computing software (e.g. R Python MATLAB Julia)

• Familiarity with Linux/Unix in a cluster-computing environment is required.

• Demonstrated experience in processing data from large scale genomic and genetic platforms such as transcriptomic epigenetic proteomic or Next Generation sequencing data including understanding of pathway/network analyses and gene regulation.
• Solid understanding of statistical methods relevant to large scale analysis of biological data sets
• Experience designing analyzing and interpreting single cell multiomics experiments including single cell RNA-seq single cell ATAC-seq and single cell methylation profiling is a significant plus.
• Knowledge of and experience with common bioinformatics databases resources and tools.
• Knowledge of fundamental concepts in biology and statistics. Experience in oncology or immunology research is desirable
• Able to communicate and collaborate effectively with scientists across a broad range of disciplines

• Strong organizational techniques including the ability to handle a variety of tasks in a fast-paced environment

The ideal candidate will be passionate about advancing scientific discovery a team player and highly self-motivated. A minimum two-year commitment is required with appointment to commence in Spring/Summer of 2022.

At Dana-Farber Cancer Institute we work every day to create an innovative caring and inclusive environment where every patient family and staff member feels they belong. As relentless as we are in our mission to reduce the burden of cancer for all we are equally committed to diversifying our faculty and staff. Cancer knows no boundaries and when it comes to hiring the most dedicated and diverse professionals neither do we. If working in this kind of organization inspires you we encourage you to apply.

Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race color religion sex gender identity or expression national origin sexual orientation genetic information disability age ancestry military service protected veteran status or other groups as protected by law.