HMS - Postdoctoral Fellow in Genetcs

Harvard University; Boston (MA); On-site; USD 65,000 - 75,000; Full time

Job summary

Harvard Medical School’s Perrimon lab seeks a highly motivated post‑doc trainee to design and implement bioinformatics pipelines for RNA-seq and multi-omics data, collaborating with DRSC/TRiP core and a multidisciplinary team.

You will contribute to data processing, algorithm development, and integration with databases, while documenting methods and supporting grant and manuscript preparation.

Qualifications

• Doctoral degree in bioinformatics or biology with omics experience.
• Strong programming, algorithms and statistics background.
• Experience with BIG DATA (NGS) and multi-omics datasets.
• Familiarity with genome alignment software such as Bowtie2/BWA/TopHat.
• Proficiency in Python and scripting languages; Unix knowledge.
• Excellent information management and collaboration skills.

Responsibilities

• Design and implement reusable bioinformatics pipelines for RNA-seq, scRNA-seq, genomics and proteomics data.
• Apply computational and AI/ML approaches to reveal biological insights.
• Develop custom databases, web portals and data pipelines for raw/processed data.
• Collaborate with investigators and teams to define scope and timelines.
• Document procedures, prepare summary reports and contribute to grants/manuscripts.

Skills

Bioinformatics

Programming

Statistics

Python

Linux/Unix

Collaboration

Education

Doctoral degree

Tools

Bowtie2

BWA

TopHat

Job description

We are seeking a highly motivated post‑doc trainee to join Dr. Norbert Perrimon’s group in the Program of Genetics at Harvard Medical School. Perrimon lab is actively generating data sets of omics scale and this position will involve working with other post‑doc trainees in the lab who are responsible for designing and generating such datasets. In addition, this position involves working with DRSC/TRiP functional genomics core, a multi‑disciplinary team of biologists, software engineers and bioinformaticians as we develop and leverage technological breakthroughs to explore the biology of complex systems.

Principal Responsibilities

• Design and implement reusable bioinformatics analysis pipelines for processing RNA‑seq, single‑cell RNA‑seq, genomics and proteomics data. Develop novel algorithms and integrated data‑visualization applications when existing software packages are not available or are not adequate.
• Apply computational, statistical, and AI/ML approaches to uncover biological insights and support functional discovery by analyzing multi‑omics datasets (eg. genomics, transcriptomics, proteomics, metabolomics, and related datasets).
• Help develop custom databases, web portals and pipelines for managing raw and processed experimental data as well as reagent identification/designs.
• Collaborate closely with the investigator and lab members on research projects, including defining the scope of the collaboration, researching the scientific topics and implementing the appropriate bioinformatics solutions that meet project timelines. Coordinate and collaborate with other bioinformaticians, biostatisticians, IT professionals, and interdepartmental project teams.
• Properly document the procedures used in computational analysis, provide summary reports of results, and contribute to grant and manuscript writing.

Salary and Benefits

This position is salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post‑PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines. With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes of collective bargaining and matters affecting your compensation and working conditions.

Basic Qualifications

• Doctoral degree in Bioinformatics or in biology with extensive experience analyzing omics data.
• Strong background in programming, algorithms and statistics.
• Familiarity with programming techniques for analyzing data sets and experience working with BIG DATA (eg. NGS data in multi‑TB scale).
• Experience using genome alignment software (bowtie2, bwa, tophat, etc.) is desired.
• Fluent in one programming language (Python, C, C++ or Java) and familiarity with scripting languages (bash, Perl).
• Knowledge of Unix operating system, terminal and bash is a plus.
• Experience using a compute cluster.
• Excellent information management skills.

Additional Qualifications

• Experience using relational databases, SQL and/or structured data formats.
• Web programming experience (PHP, Django, JavaScript, jQuery, JSON, REST API) is a plus.
• Excellent oral and written communication skills as well as the ability to collaborate effectively with a diverse team.

EEO/Non‑Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non‑discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes. Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non‑discrimination policy. Harvard’s equal employment opportunity policy and non‑discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.