Senior Scientist, Machine Learning

Cambridge, MA /
Computational Biology /
The Company
Rheos Medicines is a precision medicine company using insights from immunometabolism to bring novel therapeutics to patients suffering from autoimmune diseases. The company’s approach elucidates the underlying complexities and heterogeneity of immune mediated disease via a proprietary platform and product engine that integrates multiple “-omic” datasets through a metabolic lens. Rheos systematically defines the biologic links between immune cell metabolism and function across patient subsets and advances novel biomarker-enabled small molecule therapeutics to bring precision to the treatment of immune-mediated diseases. In December 2019, we entered a worldwide collaboration with Roche to identify and develop new therapeutics for autoimmune and inflammatory disease. Rheos was founded by Third Rock Ventures and is located in Cambridge, MA

The Role
We are looking for a highly motivated, collaborative, and innovative Machine Learning Scientist who will work at the intersection of multiple key areas of drug discovery: machine learning, bioinformatics, computational biology, immunology, and systems biology. This individual will play a key role in advancing Rheos’s machine learning engine to drive target discovery through analysis and integration of multi-dimensional datasets, combining our proprietary platform with publicly existing data sets, and developing novel models for graph-based machine learning, text mining, and clinical data. This position will be one of high visibility withing the company, where the successful candidate will partner with hers/his colleagues in the Computational Biology and Bioinformatics team, with members of the Research Informatics team, as well as colleagues in Cellular Metabolism, Biology, and Chemistry functions at Rheos.

·        Develop and implement machine learning methods on graphs
·        Implement machine learning and deep learning technologies for the identification of biomarkers and to perform patient stratification
·        Implement machine learning technologies to mine unstructured data linking clinical outcomes and patient data to multi-omics biomarkers
·        Use machine learning methods to help in the design of clinical trials for precision medicine applications
·        Close collaboration with cell biologists, metabolomics experts and company academic founders on a myriad of projects
·        Develop new predictive tools to be used across the organization, from data scientists to bench biologists and executive team
·        Participate in project teams and contribute to experimental design and data analysis, interpretation and communication of results
Requirements and Qualifications
·        PhD in Statistics, Mathematics, Computational Biology, Bioinformatics, Computer Science or a related field with 3+ years’ work experience or MS with 8+ years relevant work experience
·        Extensive experience with machine learning technologies and implementation of deep learning architectures, with a proven track record
·        Experience with graph convolutional networks, natural language processing, CNN, RNN architectures
·        Expertise in computational biology/bioinformatics is a must
·        Understanding of principles from network biology and cellular metabolism is a plus
·        Hands-on experience in development of interactive tools for a non-technical audience (R Shiny, Python, Dash)
·        Hands-on experience in data curation and harmonization of public biological and biomedical databases
·        Outstanding programming skills in R or Python
·        Expertise with cloud computing (AWS/GCP) and SQL
·        Expertise with good practices for reproducible research (git, Jupyter notebooks)
·        Excellent written and oral communication skills
·        Prior experience in biotech/pharma industry in drug discovery, including exposure to (computational) medicinal chemistry
·        Experience in computational pipelines for analysis of complex omics datasets, such as single-cell RNA-Seq, ATAC-Seq, proteomics, metabolomics
·        Experience in integrative analysis of multi-dimensional omics data 
Rheos Medicines is proud to be an equal opportunity employer and to provide equal opportunities to all employees and applicants for employment without regard to race, color, religion, sex or gender identity, national origin, age, disability, sexual orientation or genetics. In addition to federal law requirements, Rheos Medicines complies with applicable state and local laws governing nondiscrimination in employment.