This fellow will be responsible for developing novel statistical genetics methods to drive the understanding of human complex disorders. More specifically, we are interested in developing fine-mapping and polygenic risk prediction methods to integrate large-scale genomic data from a diverse range of ancestries, and methods focusing on elucidating the contribution of rare variants in complex disorders. Being part of several consortia, our group has access to large-scale genomics data on psychiatric and autoimmune disorders across the world.

The candidate should have a strong computational background, good publication history, knowledge of current research methods, and be able to adapt quickly and be part of a cross-functional team in a rapidly changing environment.

The Analytic and Translational Genetics Unit provides a vibrant multidisciplinary research environment with close links to the Broad Institute, MIT, Harvard and the Harvard-affiliated hospitals. As a member of our group, you will be provided the opportunity for your contributions to be utilized and recognized across the vast global network of researchers in the fields of genomics and complex disease research.

QUALIFICATIONS

· PhD required in mathematics, statistics, computer science, bioinformatics, human genetics or other biomedical sciences.

· Good publication history in computational biology, genetics or epigenetics research.

· Strong initiative and ability to take ownership of assigned tasks and projects essential.

· Solid understanding of genetic analysis methodologies and tools, and/or computational methods frequently used in analyzing the regulatory genome.

· Understanding of population genetic is a plus.

· Practical experience with Linux environments and proficient in a least one of the following programming languages:  Java, C, MATLAB, R, Stata or Python.

· Demonstrated attention to detail and analytical skills.

· Excellent communication and interpersonal skills.

· Excellent written and oral presentation skills.

CANDIDATES

Please send your CV and cover letter to Dr. Hailiang Huang (hhuang@atgu.mgh.harvard.edu). In your cover letter please include at least three references who are familiar with your academic performance and/or research experiences.

哈佛大学附属医院