Postdoctoral Fellow — Computational RNA Biology & Cancer

Dana-Farber Cancer Institute (DFCI); Boston (MA); Presencial; USD 72.000 - 76.000; Tempo integral

Resumo da vaga

Dana-Farber Cancer Institute in Boston, MA, invites applications for a Postdoctoral Research Fellow in the Insco Laboratory. The role focuses on computational RNA biology and cancer, with a team-driven environment supporting independent projects and mentorship opportunities.

The successful candidate will analyze transcriptomic datasets, develop computational tools, and contribute to publications while collaborating with clinicians and researchers across the Institute.

Qualificações

• PhD or equivalent in biomedical/computational sciences.
• Experience analyzing complex transcriptomic or functional genomics datasets.
• Proficiency in Python and R with HPC experience.
• Desirable: RNA biology and cancer biology background; interest in computational modeling.

Responsabilidades

• Apply existing computational tools to analyze transcriptomic and functional genomics datasets.
• Develop new computational tools to study the dark transcriptome in cancer.
• Develop reproducible computational workflows and ensure code/data deposition in public repositories.
• Help manage the lab’s data, computational infrastructure, and bioinformatics resources.
• Prepare applications for fellowships and contribute to lab grant applications; lead research projects.
• Mentor trainees in computational biology and maintain organized research records.
• Interpret and discuss findings in lab meetings; develop figures to communicate results.
• Write original research manuscripts and review articles; present findings at conferences.

Conhecimentos

Python

R

HPC usage

RNA biology

Formação

PhD or equivalent doctoral degree

Descrição da vaga

Dana-Farber Cancer Institute in Boston, MA, invites applications for a Postdoctoral Research Fellow in the Insco Laboratory. The role focuses on computational RNA biology and cancer, with a team-driven environment supporting independent projects and mentorship opportunities.

The successful candidate will analyze transcriptomic datasets, develop computational tools, and contribute to publications while collaborating with clinicians and researchers across the Institute.