[updated May 2022]
Applications are invited for multiple positions in the Park laboratory (https://compbio.hms.harvard.edu) in the Department of Biomedical Informatics at Harvard Medical School. The aim of the laboratory is to develop and apply innovative computational methods for genome sequencing data to enhance our understanding of cancer genetics, neurogenetics, and epigenetics.
Recent work from the laboratory includes methods for detection of mosaic mutations from single cell and bulk WGS data (Dou et al, Nat Biotech, 2020; Bohrson et al, Nat Gen, 2019) and their applications (Bizzoto et al, Science, 2021; Lodato et al, Science, 2018), mutational signature analysis (Gurhan et al, Nat Gen, 2019), and analysis of chromothripsis events across cancers (Ciriano-Cortes et al, Nat Gen, 2020).
Several positions are available immediately. Areas of interest include
- Identification of mosaic mutations in non-tumor cells and application to lineage tracing
- Mutational signature analysis for cancer/brain samples
- Cancer Research UK “Grand Challenge” on why cancer mutations are tissue type-specific
- Analysis of repetitive elements and 3D genome organization
An ideal candidate will have a PhD in computational biology/bioinformatics/statistics/CS or another quantitative field, as well as excellent programming and communication skills. Experience in analysis of high-throughput sequencing data is highly desirable. Those without bioinformatics experience but have a very strong quantitative (math/physics/stat) background will also be considered.
The successful candidates will join a group of supportive and productive computational biologists and have an opportunity to collaborate with world-class biologists in the Harvard medical area. Many of our fellows have gone on to faculty positions at top institutions, including three at Harvard.
Please send your CV with '[POSTDOC]' and your name in the subject line. A research statement that demonstrates one's expertise in an area is helpful but not required.
Junior Scientific Programmers
One or two positions are available for those who finished college and are looking for research experience before going on to graduate or medical school. They will assist postdoctoral fellows with various research projects and, if desired, engage in their own research. The past programmers have gone on to graduate schools at Harvard, MIT, Stanford, and Oxford as well as medical schools.
There are multiple openings for graduate students. The student must already be enrolled in a graduate program at Harvard (Bioinformatics and Integrative Genomics, Biophysics, Biological and Biomedical Sciences, etc) or at MIT (Health Sciences & Technology, etc). Inquires regarding graduate student positions from those not already enrolled in one of these programs will go unanswered.
Visiting graduate positions may be available; there are no internship positions for foreign medical students.
Undergraduate Research Assistants
A small number of research positions are open for undergraduates throughout the year. A 10-hour commitment during school year and a full-time commitment during summer are required. Strong quantitative background and substantial programming experience are essential. You may also be interested in the Summer Institute in Bioinformatics and Integrative Genomics at Harvard-MIT Health, Science and Technology.
We are seeking a motivated Data Curator to join the Department of Biomedical Informatics at Harvard Medical School, and become a key part of the 4DNucleome Data Coordination and Integration Center (4DN-DCIC).
The 4DN Network is an NIH consortium (https://commonfund.nih.gov/4dnucleome) that applies the newest technology in DNA sequencing and imaging to investigate the principles underlying the dynamics of nuclear organization and the role nuclear organization plays in human disease. The 4DN-DCIC collects, curates, stores, and processes the data generated by the Network and maintains the 4DN data portal: https://data.4dnucleome.org/
The data wrangler will help maintain and extend the 4DN data model, including implementation of health-related data model extensions. They will interact with 4DN Network data generators to assist in submission of metadata and data to the portal. They will also participate in the specification, design, and implementation of tools that integrate, search, and display the data, working closely with bioinformatic scientists and software engineers. The successful candidate must be able to learn and work independently, yet collaborate effectively with co-workers.
The ideal candidate has a strong background in molecular biology and experience working with sequencing data. They enjoy coding and being involved in software development, and have a penchant for data/metadata management and organization.
Join a multidisciplinary team of biologists, bioinformatic scientists and software engineers in a working environment that combines the best features of a startup (fast pace, flexibility, flat hierarchies) with those of one of the leading medical schools (excellent benefits, outstanding opportunities for learning, great resources, brand recognition).
Required skills & experience
- PhD in Biology, Bioinformatics, or a related field, or a master’s degree and 3 years' experience in data curation.
- Technical expertise in genetics, molecular biology, bioinformatics, microscopy or a related field.
- Excellent organizational skills and attention to detail.
- Strong verbal and written communication skills.
- Experience with basic computer programming / scripting languages.
- Working knowledge of Python.
- Project management skills including team management, issue management, and change management.
- Experience with using ontologies and controlled vocabularies
- Ability to understand scientific literature, experimental procedures and their limitations, and current needs of the research community.
We are also seeking a staff bioinformatics scientist to be part of the 4DNucleome Data Coordination and Integration Center (https://data.4dnucleome.org/help/about/about-dcic). This individual will implement, test, and optimize various bioinformatics pipelines for processing epigenetic and other datasets on Amazon Web Services. Postdoctoral experience is desirable but not required.
We are also hiring software engineers interested in using their skills to help build a whole-genome analysis platform for researchers and physicians. Experience in bioinformatics is helpful but not required. International applicants with at least a master’s degree are welcomed; remote work is a possibility.
To the applicants to the BIG PhD program :
Many of you are sending me emails with CVs to express your interest in the Bioinformatics & Integrative Genomics PhD program (http://dms.hms.harvard.edu/big/); some of you are asking to meet with me. I am delighted that you are interested in the program. But the admission decisions are made by the admissions committee after carefully examining all the application materials (including recommendation letters, transcripts, test scores, personal statement) submitted via the official application portal (https://gsas.harvard.edu/admissions). Therefore, I do not make judgment on one's CV alone and do not comment on anyone's chances or provide suggestions.
Please note that the committee selects our incoming class without regard to a specific advisor with whom the student wishes to work (if the applicant indicates any). Every student is funded for the first two years by the school (including by a grant from NIH), rather than by a specific laboratory, in order to provide an opportunity for the student to explore. Therefore, showing an interest in a particular professor's laboratory in the hopes that the professor would speak on the student's behalf is not likely to be helpful for the admissions decisions.
As to the question of whether I am accepting students, the answer is yes, But I do not discuss potential research projects with students until they are admitted. So far, I have accepted all BIG students who wished to join my laboratory.
I am sorry that I am unable to respond to individual queries due to the heavy volume of emails I receive.