Our interdisciplinary team designs computational methods to draw medically relevant conclusions from genomic data sets. This particular project is focused on applying such techniques to developing novel prenatal diagnostics and suggesting therapeutic interventions. Our goals include designing methods to mine new functional annotation specific to the early stages of human development and applying this annotation in clinical data analysis. This work heavily incorporates data mining and machine learning methods. We are looking for a postdoctoral researcher to be a substantial contributor to this project.
The successful candidate will have a Ph.D. in computer science, bioinformatics, or a closely related field, and experience working with high throughput gene expression, genotyping, next-generation sequencing, or other large-scale genomic data sets. Ability to design algorithms and rapidly implement and evaluate them is essential. Machine learning expertise a significant plus. Familiarity with genomic functional annotation databases such as the Gene Ontology is extremely desirable. Applicants should have a demonstrated ability to perform research both independently and as part of a team, excellent communication skills including the ability to read and understand the relevant biomedical literature, and an interest in the potential clinical applications of our work.
This project is based in the lab of Prof. Donna Slonim, whose primary appointment is in the Computer Science Department at Tufts University, and is a collaboration with the lab of Dr. Diana Bianchi, Vice-Chair for Research and Professor of Pediatrics at Tufts Medical Center.
Interested candidates should submit a CV, names of three references, and a brief cover letter
summarizing interest and qualifications through the Academic Jobs Online web site:
https://academicjobsonline.org/ajo/TuftsCS/ComputerScience/131
Donna Slonim
http://www.cs.tufts.edu/~slonim/