Biostatistician Principal

## Biostatistician Principal Apply remote type:
Hybrid locations:
Boston-MAtime type:
Part time posted on:
Posted Todayjob requisition :
RQ4075343

Site:
The Brigham and Women's Hospital, Inc.

Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
** Job Summary
** The Chai Laboratory seeks a doctoral-level Senior Computational Scientist to provide specialized, intermittent computational leadership to an active portfolio of epigenomics and hematologic malignancy projects. This is a per diem appointment created to sustain continuity of a highly specialized analytical program during a defined interval, and to carry several late-stage manuscripts through revision, resubmission and publication.  The laboratory’s epigenomics program is built on a proprietary set of internally developed analysis with no commercial or off-the-shelf equivalent.

The successful candidate will act as the technical maintainer of these frameworks and as computational co-investigator on the studies that depend on them.  As the appointment is intermittent, part-time and tied to manuscripts already under review, the candidate must be able to contribute productively from the first billed hour.
** Qualifications
* * Education  Master's Degree Statistics required or Master's Degree Related Field of Study required    Can this role accept experience in lieu of a degree?  Yes    Experience
* PhD in bioinformatics, computational biology, cancer genetics or a closely related discipline, with a expertise in hematologic malignancy.
* Formal degree-level training in computer science or software engineering. The role requires maintenance and release engineering of production research software used outside this institution, not scripting-level analysis alone.
* Formal training in diagnostic pathology or an equivalent wet-laboratory discipline, with demonstrated independent bench capability. The role requires unsupervised interpretation of computational results against experimental design, without an intermediary.
* Minimum seven (7) years of post-doctoral research experience in myeloid malignancy epigenetics.
* Demonstrated first, senior or corresponding authorship of published, publicly maintained NGS analysis pipelines that are in documented use by laboratories outside the author’s own institution.
* Direct experience with methylation-domain discovery.
* Peer-reviewed publication record commensurate with senior scientific standing, to include first-authorship and senior/corresponding authorship in journals of the highest impact tier, and demonstrated productivity in hematology, epigenetics and cancer metabolism.
* Existing academic appointment at the rank of Instructor or above.
* Immediate availability, current U.S. work authorization. The intermittent per diem structure does not permit a training or onboarding period.
* Advanced proficiency in R, Python and Unix/Linux shell environments, and competence in HPC and cloud-based analysis at multi-terabyte scale.
** Preferred
* ** Experience with leukemia models, and with DNMT3A-mutant AML biology.
* In vivo hematopoiesis experience, including conditional-knockout murine bone marrow handling experience.
* Peer-review service for scientific journals.
* University-level teaching experience and demonstrated ability to communicate technical results to non-specialist audiences.
** Knowledge,

Skills and Abilities

***
* Key Responsibilities:

*** Serve as lead computational scientist and technical owner of the laboratory’s DNA methylation regulatory-element program.
* Maintain, extend, debug and version the laboratory’s published analysis pipelines.
* Analyze and integrate multi-omic datasets: WGBS/RRBS, ChIP-seq, CUT&RUN, ATAC-seq, RNA-seq, RIP-seq, single-cell RNA-seq and CITE-seq, and long-read…