Postdoctoral Fellow- Meyerson Lab

The Meyerson Lab at the Broad Institute of MIT and Harvard and Dana-Farber Cancer Institute is seeking a highly motivated postdoctoral fellow to develop and apply computational approaches to understand the genomic basis of human cancer and translate these discoveries into improved therapeutic strategies.

Our laboratory uses genomic and genetic approaches to investigate the causes of human cancer with a particular focus on lung cancer and other epithelial malignancies. Through these studies we seek to understand the biological consequences of genomic alterations that drive tumor initiation progression and therapeutic response and to identify vulnerabilities that can be exploited therapeutically.

The successful candidate will lead an independent research project focused on the discovery and characterization of somatic alterations in cancer genomes with particular emphasis on alterations occurring in the non-coding genome. The fellow will analyze large-scale cancer genome datasets generated from both short-read and long-read whole genome sequencing technologies integrating information from tumor DNA and matched normal DNA to identify novel classes of cancer-associated genomic variation.

Potential project areas include:

Discovery and characterization of somatic non-coding mutations and structural variants that contribute to tumorigenesis.

Development of computational methods for analysis of short-read and long-read whole genome sequencing data from cancer and matched normal samples.

Identification and interpretation of complex structural variation copy number alterations chromosomal rearrangements and mutational processes in cancer genomes.

Integration of genomic transcriptomic and epigenomic datasets to determine the functional consequences of non-coding genomic alterations.

Application of statistical and machine learning approaches to improve detection and interpretation of somatic variation in cancer.

Investigation of genomic mechanisms underlying cancer development progression and therapeutic resistance particularly in lung cancer.

The ideal candidate will have a Ph.D. in Computational Biology Computational Genomics Bioinformatics Statistical Genetics Computer Science Biostatistics or a related quantitative discipline with extensive experience in genome analysis and cancer genomics.

Preferred qualifications include:

Strong experience analyzing whole genome sequencing data.

Experience working with somatic variant calling pipelines for SNVs indels copy number alterations and structural variants.

Familiarity with short- read and long-read sequencing technologies such as Oxford Nanopore or PacBio and their applications in cancer genomics.

Experience with genomic data processing tools and workflow management systems in high-performance computing environments.

Responsibilities will include designing and leading research projects developing and implementing computational methods analyzing and interpreting genomic datasets preparing manuscripts and presentations collaborating with experimental and computational scientists across the Broad Institute and Dana-Farber Cancer Institute and contributing to a collaborative and intellectually stimulating research environment.

Candidates should have aPh.D. M.D./Ph.D. or equivalent degree in a relevant fieldwith 0-2 years of experience in an academic setting. Strong communication skills intellectual curiosity and the ability to work both independently and collaboratively are essential.