Postdoctoral Research Fellow - Insco Lab

Dana--farber-Cancer-Institut; Boston (MA); On-site; USD 72,000 - 76,000; Full time

Job summary

Dana-Farber Cancer Institute, Inc. invites applications for a Postdoctoral Fellow in Computational RNA Biology and Cancer. The candidate will analyze complex transcriptomic datasets and build novel computational tools under joint mentorship with Dr.

David Liu. Work spans direct RNA sequencing, Ribo-seq, PAR-CLIP, and single-cell data to uncover RNA-driven oncogenic mechanisms. Located in Boston, the role emphasizes rigorous data analysis, manuscript preparation, and collaboration within a

Qualifications

• PhD or equivalent doctoral degree in biomedical, computational, or related sciences.
• Experience analyzing complex transcriptomic or functional genomics datasets.
• Proficiency in Python and R, with HPC experience to analyze large datasets.
• RNA biology, transcriptional biology, and/or cancer biology background desirable.

Responsibilities

• Apply computational tools to analyze transcriptomic and functional genomics datasets.
• Develop new computational methods for dark transcriptome studies in cancer.
• Create reproducible workflows and share code and data in public repositories.
• Manage lab data, computational infrastructure, and bioinformatics resources.
• Prepare fellowship applications and contribute to grant proposals.

Skills

Analytical thinking

Scientific writing

Communication skills

Mentoring

Education

PhD in biomedical/computational sciences

Tools

Python

R

HPC

Job description

Postdoctoral Fellow in Computational RNA Biology and Cancer

A postdoctoral fellow position is available in the Insco Laboratory in the Department of Medical Oncology at Dana-Farber Cancer Institute (DFCI). We are seeking an enthusiastic and highly motivated scientist to join our team!

The Insco Lab investigates how aberrant RNA processing and defects in nuclear RNA quality control contribute to cancer, with a particular focus on melanoma. We are especially interested in the dark transcriptome, including aberrant RNAs derived from repetitive genomic elements and mis-spliced transcripts. By combining zebrafish models, mechanistic studies in human melanoma cell lines, and analyses of patient-derived datasets, we seek to uncover clinically relevant RNA-driven oncogenic mechanisms and identify therapeutic vulnerabilities in high-risk melanoma. Our lab fosters a culture of curiosity, rigor, collaboration, and teamwork. Each scientist leads an independent project while benefiting from the collective expertise and support of the group. As a physician-scientist-led laboratory, we are committed to discovering and targeting patient-relevant mechanisms, providing individualized mentorship, and helping each lab member achieve their professional goals both during their time in the lab and beyond.

This position will be jointly mentored by Dr. David Liu at DFCI. Dr. Liu is a melanoma medical oncologist and translational scientist with a background in software engineering. His laboratory develops biologically informed predictive models using statistical and machine-learning approaches. The successful candidate will analyze cutting-edge transcriptomic datasets from model organisms and patient samples. These may include data generated using Oxford Nanopore direct RNA sequencing, PAR-CLIP, ribosome profiling (Ribo-seq), single-cell RNA sequencing, and DMS-MaP. Projects may involve dark transcriptome annotation, peptide prediction, RNA modification analysis, and RNA structure analysis.

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.

RESPONSIBILITIES

• Apply existing computational tools to analyze transcriptomic and functional genomics datasets, including short-read RNA-seq, direct RNA sequencing, PAR-CLIP, DMS-MaP, and ribosome profiling (Ribo-seq).
• Develop new computational tools to study the dark transcriptome in cancer.
• Develop reproducible computational workflows, document and share code, and ensure the appropriate deposition of code and data in public repositories.
• Help manage the Insco Lab’s data, computational infrastructure, and bioinformatics resources.
• Prepare applications for individual fellowships, contribute to laboratory grant applications, and lead research projects.
• Think independently and creatively while collaborating effectively with the team.
• Mentor trainees in computational biology.
• Maintain detailed, well-organized, and accessible research records.
• Interpret and discuss research findings both informally and in lab meetings.
• Develop figures that clearly communicate research findings.
• Write original research manuscripts and review articles, and present findings at scientific conferences.

QUALIFICATIONS

• Accomplished and motivated candidates with a PhD or equivalent doctoral degree in the biomedical, computational, or related sciences are encouraged to apply.
• Applicants should have experience analyzing complex transcriptomic or functional genomics datasets.
• Proficiency in Python and R, along with experience using high-performance computing environments to analyze large-scale biological datasets, is required.
• Experience in RNA biology, transcriptional biology, and/or cancer biology is desirable, and interest or experience in computational modeling of protein complexes is a plus.
• Candidates must demonstrate strong critical-thinking, scientific writing and communication skills, as well as a record of scientific accomplishment that includes at least one peer-reviewed original research publication.

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 committed to having faculty and staff who offer multifaceted experiences. Cancer knows no boundaries and when it comes to hiring the most dedicated and compassionate 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 characteristics protected by law.

Pay Transparency Statement

The hiring range is based on market pay structures, with individual salaries determined by factors such as business needs, market conditions, internal equity, and based on the candidate’s relevant experience, skills and qualifications.

For union positions, the pay range is determined by the Collective Bargaining Agreement (CBA).

$72,000.00 - $76,385.00