The ideal candidate has both a theoretical and practical understanding of machine learning techniques and has a proven track-record in areas such as computational biology, probability, statistics, complex networks data analysis, statistical physics, or high-performance computing.The candidate joins a strong team of data scientists to work with, has access to vast amounts of omics data, and is encouraged to publish new methods and results in academic journals and conferences.

This position is suited to a person who is excited by the prospect of learning, adapting and applying modern machine learning techniques to solve the key challenges for emerging biological data modalities, with revolutionary implications in advancing the state-of-the-art clinical practice.

Responsibilities

-Adapting and applying existing machine learning techniques to omics datasets

-Developing novel machine learning methods for understanding and organizing unstructured datasets

-Developing robust and generalizable inference algorithms that advance the state-of-the-art

-Writing well-crafted, maintainable, scalable, and performant machine learning code

-Designing, developing, and maintaining tests framework for machine learning code

Requirements

-Ph.D. in Computational Biology, Computer Science, Physics, Math, Statistics, or related quantitative fields

-Strong communication skills and ability to collaborate with biologists, computational biologists, data scientists, and software engineers on model requirements and design

-Scientific and numerical programming in Python or R

-Strong bash/shell scripting and proficiency with UNIX operating systems

-Familiarity with one object-oriented programming language (e.g. Java, C++, Go)

Preferred Skills

-0-2 years post-Ph.D. experience working on machine learning or a related area

-Working knowledge of existing machine learning and probabilistic programming infrastructures (e.g. Theano, TensorFlow, PyTorch)

-Fluency with version control, including distributed version control and Git in particular

The Broad Institute will offer visa sponsorship for this opportunity.

All Broad employees, regardless of work location, must be fully vaccinated for COVID-19 by Tuesday, October 12, 2021. Requests for exemption for medical or sincerely held religious beliefs will be considered.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

EEO is the Law Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled