Postdoctoral Fellow - Huttenhower lab

Description & Requirements

The Broad The Broad Institute of MIT and Harvard is one of the world's leading biomedical research institutes. It seeks to discover the molecular basis of major human diseases, develop effective new approaches to diagnostics and therapeutics, and disseminate discoveries, tools, methods, and data openly to the entire scientific community.

Founded in 2004, the Broad Institute includes faculty, professional staff, and students from throughout the MIT and Harvard biomedical research communities, with collaborations spanning the globe.

The Lab The Huttenhower lab in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health and the Broad Institute of MIT and Harvard ( is seeking a Research Scientist.

The Research Scientist will be responsible for performing and overseeing research in the area of computational discovery, prioritization, and characterization of potential bioactives from the microbiome as part of the Human Microbiome Bioactives Resource (HMBR) and NIDDK-funded platform for therapeutic characterization from the gut.

Potential bioactives include whole organisms (microbial taxa or strains), gene products, secreted peptides, biosynthetic operons, or small molecule metabolites.

The Huttenhower lab is broadly engaged in methods development and applied studies of the roles of the human microbiome in health and disease, with a focus on computational approaches to characterize biomolecular functions within these microbial communities and their interactions with host immunity and health.

The group works closely with the Harvard Chan School, the Broad Institute, the Dana-Farber Cancer Institute, and the broader Boston biomedical and life sciences communities, resulting in a rich environment for quantitative, computational, and laboratory collaborations. Job Responsibilities

Develop new methods for predicting enzyme-substrate relationships from among prioritized bioactives, drawing on 1) metagenome, metatranscriptome, and metabolome data integration and meta-analysis;

2) computational enzyme and small molecule function prediction; and 3) molecular modeling.

• Mentor trainees / junior scientists in the continued development and application of existing software systems developed for bioactive prioritization and characterization.
• Coordinate with experimental co-investigators in efforts to screen and validate potential bioactives, and to provide data and analysis support to related co-investigator-led projects.
• Make substantial contributions to manuscripts describing the above work, and to new funding applications drawing upon the above work as preliminary data.
• Prepare and / or deliver presentations describing the above work at internal and external meetings.

Qualifications

• Doctoral degree in Computer Science, Statistics, Biostatistics, Bioinformatics, Biology, or a related field.
• 2-3 years of postdoctoral training in one of the above fields or equivalent industry experience.
• Demonstrated proficiency in one or more statistical or scripting languages appropriate for scalable data analysis (R and / or Python preferred).
• Demonstrated expertise in computational methods development for biological data analysis, including experience in cluster / distributed computing environments and comfort with terabyte-scale datasets.
• Familiarity with functional genetic and / or genomic data, as indicated by publication record.
• Experience mentoring trainees and directing project groups.
• The ability to communicate scientific material clearly and collaborate well.
30+ days ago