Associate Computational Biologist

Dana-Farber Cancer Institute•Boston, MA

64d•$60,000 - $67,466•Onsite

About The Position

The laboratory of Zuzana Tothova, MD, PhD is a multi-disciplinary team of physician scientists, scientists and computational biologists at the Dana-Farber Cancer Institute and the Broad Institute. Our laboratory uses genomics and a range of molecular and cellular biological techniques to elucidate the molecular basis of cancer and hematologic disorders and to develop novel therapeutics. Our specific focus is to understand the role of chromatin modifiers and epigenetic factors and find novel therapeutic opportunities in myeloid malignancies, including myelodysplastic syndromes and acute myeloid leukemia. A full-time associate computational biologist position is available in the laboratory of Zuzana Tothova, M.D., Ph.D. at Dana-Farber Cancer Institute. We are seeking enthusiastic, self-motivated individuals who thrive in a fast-paced, challenging research environment, and can interact well with others as part of a cohesive team. If you have a desire to make a significant impact in healthcare and have the fortitude to work hard, you will succeed within this team. This is an ideal entry-level or mid-level position into the world of cutting-edge laboratory research. A growth mindset and a willingness to take on challenging learning opportunities will be sought out traits. Ideal candidates will possess strong interpersonal skills along with a desire to help others to succeed. Previous team members have gone on to successful academic and career opportunities; graduate/medical school and industry. The candidate will be involved in a series of research activities, including computational analysis of large-scale data sets generated in in vitro and in vivo human disease relevant models and use of next generation sequencing with a special emphasis on understanding the biology of human myeloid malignancies. The Associate Computational Biologist is training to become a Computational Biologist. They are responsible for routine data analysis or processing of biological data, with a focus on high-throughput technologies and genomic databases, under the supervision of mentor. The Computational Biologist is a quantitative scientist who collaborates with scientific investigators and with other research staff in the analysis of high-throughput data, and dissemination of scientific results. The Computational Biologist may work on many types of projects and areas of research including cancer genomics, functional genomics, immuno-oncology, molecular imaging, data management and integration, and querying biological databases. We are looking for candidates with at least 2 years of availability. 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.

Requirements

Minimum Education: Bachelor's degree in a computer science or related-STEM field required.
Minimum Experience: No prior experience required.
Computational Skills: Knowledge of UNIX/Linux.
Proficiency with scripting in Python and statistical programming using R.
Data analysis Skills: Familiarity with principles of experimental design and the modern data analysis paradigms is required.
Collaboration: Able to discuss and present results, share ideas accurately and communicate them effectively, both in writing and verbally with supervisory oversight.
Strong interpersonal skills - ability to effectively interact with all levels of staff and external contacts.
Excellent analytical, organizational and time management skills.
Passion for science and strong motivation required.
Must be a strong team player.
Strong interpersonal, communication and organizational skills, including the ability to handle a variety of tasks in a fast-paced environment, positive attitude and attention to detail, as well as ability to think on one's feet are required.
Must possess a high level of initiative, curiosity and dedication, proactivity in identifying problems and solutions to address them.

Nice To Haves

Familiarity with bioinformatics data types and software preferred
Familiarity with GitHub and HPC preferred
Familiarity with bioinformatics data types (e.g. FastQ, BAM, BigWig) and software (e.g. DeepTools, MACS, HOMER) preferred.
Familiarity working with Git repositories preferred.
Familiarity with computational methods for single-cell sequencing data preferred.

Responsibilities

Data Processing Builds data processing pipelines to convert raw data into formats compatible with conventional statistical analysis and visualization under supervision of mentor.
Data Analysis: Follows a detailed manual to perform routine.
Data and Software Management: Monitors, downloads, organizes, and manages data from public data repositories or generated by collaborates.
Manuscript Preparation: Helps prepare tables and figures.
Research Portfolio Management: Trains to develops timelines and components for multiple routine projects; masters multi-tasking so that complex projects involving many interdisciplinary individuals move forward smoothly.
Works closely with postdoctoral fellows and graduate students in the lab and computational biology collaborators at the Dana-Farber Cancer Institute and the Broad Institute to analyze biological data sets, including but not limited to DNA and RNA sequencing, gene expression and transcriptome analysis, chromatin landscape profiling, and analysis of microscopy/imaging data.
Modifies and maintains existing data-processing pipelines in the lab, and develops new pipelines and tools to analyze novel forms of data, including data cleaning, normalization, and visualization.
Integrates multiple data sets to answer targeted scientific questions.
Documents and compiles findings in oral and written reports.
Attends team meetings to share results, plan projects and experiments.
Maintains and improves technical knowledge base.
Other related tasks as required.