Postdoc at Pinello Lab at Massachusetts General Hospital / Harvard Medical School

CVPL; Boston (MA); On-site; USD 55,000 - 70,000; Full time

Job summary

CVPL is seeking a Postdoc for the Pinello Lab at Massachusetts General Hospital / Harvard Medical School in Boston, Massachusetts. The successful candidate will engage in innovative computational research related to (epi)genomics, single-cell analysis, and CRISPR genome editing. This role requires a Ph.D. in relevant fields and offers opportunities to work on interdisciplinary projects involving machine learning, data mining, and cutting-edge technologies.

The ideal candidate will have publication experience and excellent communication skills, working both independently and in teams. Diversity and equality are core values of our lab, encouraging applications from underrepresented minorities.

Qualifications

• Expect to receive a Ph.D. soon in relevant fields.
• Must have excellent communication and writing skills.
• Experience in bioinformatics and data analysis is preferred.

Responsibilities

• Work on interdisciplinary projects developing computational approaches.
• Analyze and integrate sources of genetic and epigenetic variation.
• Use machine learning and data mining for NGS data analysis.

Skills

Ph.D. in Computer Science, Statistics, Genetics, Bioinformatics, Computational Biology, Mathematics, Physics

First (or co-first) author in scientific publication

Excellent communication and writing skills

Able to work independently and in teams

Education

Ph.D. in relevant fields

Tools

Python

R

Bioinformatics tools and databases

Job description

Postdoc at Pinello Lab at Massachusetts General Hospital / Harvard Medical School

The Pinello Lab at Massachusetts General Hospital / Harvard Medical School is looking for Postdoctoral candidates excited about computational challenges in (epi)genomics, single-cell analysis and CRISPR genome editing.

Massachusetts General Hospital is a teaching hospital for Harvard Medical School and one of the top-ranked hospitals nationwide. It is located in Boston, Massachusetts with close proximity to numerous other top-notch medical and research institutions including Harvard School of Public Health, Dana-Farber Cancer Institute, Boston Children’s Hospital, Massachusetts Institute of Technology (MIT), The Broad Institute of MIT and Harvard, Brigham and Women’s Hospital, Harvard Medical School, and Beth Israel Deaconess Medical Center, which fosters close interactions among faculty and fellows and a strong and rich network of collaborations and intellectual exchange.

The candidate(s) will work on interdisciplinary projects developing innovative computational approaches to systematically analyze and integrate sources of genetic and epigenetic variation and gene expression variability in human traits and diseases.

The lab uses machine learning, data mining and high-performance computing technologies such as parallel and GPU computing to solve computationally challenging and big data problems associated with next generation sequencing (NGS) data analysis. Our mission is to use computational strategies to further our understanding of disease etiology and to provide a foundation for the development of new drugs and more targeted treatments. Read more about our research, recent publications and software here: http://pinellolab.org

Requirements

• The ideal candidate(s) should have received (or expect to receive soon) a Ph.D. in Computer Science, Statistics, Genetics, Bioinformatics, Computational Biology, Mathematics, Physics, or related fields
• First (or co-first) author in one or more peer‑reviewed scientific publication
• Excellent communication and writing skills
• Able to work both independently and in teams

Preferred Skills (not required)

• Proficiency in Python and/or R
• Experience with commonly used bioinformatics tools and databases
• Experience working with different types of NGS data such as ChIP‑seq, RNA‑seq, ATAC‑seq
• Experience in the analysis of data from genome editing assays
• Experience in the analysis of single cell data
• Knowledge of commonly-used machine learning methods

Our lab is committed to diversity and equality; therefore, we encourage applications from underrepresented minorities.

Application process

If you are interested, please send your CV and a cover letter describing your current and future research interests, and the contact of 2-3 references to Luca: [e-mail]