Department/Area: Department of Immunology and Infectious Diseases
The malaria genomics group within the Infectious Disease and Microbiome Program at the Broad Institute develops and applies genomics approaches to address key questions in malaria biology and to support global malaria elimination efforts. A major focus of our group is to understand the evolution and transmission of malaria parasites in natural settings, including the development and spread of anti-malarial drug resistance. We work with research partners in malaria endemic countries, as well as national malaria control programs and health ministries to apply genomic tools and data to address epidemiological questions related to malaria elimination.
We are seeking a creative and highly motivated postdoctoral fellow to lead parasite genomic and population genetic data analysis. The successful candidate will work collaboratively with other group members to develop innovative computational approaches for genomic analyses and population genetic/epidemiological interpretation relevant to a range of malaria projects, exploiting large genomic datasets to understand mechanisms of parasite evolution, transmission, population dynamics, drug and immune evasion, and host-pathogen interactions.
Ideal applicants will have a PhD in a relevant field, with strong background in computational biology, bioinformatics, population genetics, statistical genetics, and epidemiology, ideally in the context of malaria or other infectious diseases. The successful candidate will join a diverse group that combines the expertise of malaria biologists, computational biologists, and programmers. They will be expected to both develop and lead projects independently, and to work collaboratively on ongoing projects in the group, taking into account the relevant literature, own experience, and advice from the team leader and other scientists as appropriate.
We work in a dynamic scientific environment locally within Boston, and connected to malaria research and control communities around the globe. The Wirth lab is based at both the Broad Institute in Cambridge and the Harvard T.H. Chan School of Public Health in Boston (approx 4 miles apart), the candidate would be expected to work flexibly between these connected sites.
●Perform bioinformatic analyses to extract biological meaning from large scale sequencing data, genotyping data for malaria parasites ●Research and identify proper approaches for interrogating data using primary literature ●Work collaboratively with group members scientists at the Broad, Harvard, and elsewhere to make data accessible and interpretable ●Learn, use and extend existing tools and pipelines for data analysis within the group ●Perform other duties as necessitated by the position or as assigned
PhD in relevant field, with strong background in computational biology and bioinformatics ideally in the context of malaria or other infectious diseases.
Requires proficiency in: ●Managing and processing next-generation sequencing data (BLAST, alignment, etc.) ●Next generation sequence data analysis (BWA, samtools, GATK, etc.) ●Statistical tools (R, Matlab, etc.) ●Population genetics ●Epidemiology ●Genome biology ●Malaria biology or other infectious disease ●Unix/Linux operating system ●Programming skills, such as Perl or Python
General abilities required: multi-tasking, work independently, collaborative skills, adapt to changing priorities, work in fast-paced environment, highly developed analytical and problem solving skills, oral and written communications skills, data presentation skills
Please contact Dr. Bronwyn MacInnis by email: email@example.com with CV, letter of interest, and names of at least three references.
Contact Email: firstname.lastname@example.org
Equal Opportunity Employer:
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.
Internal Number: 8178
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