Postdoctoral Fellow - Genetics Center - Data Sci and Machine Learning

The Regeneron Genetics Center (RGC) has a central goal to apply large scale human genetics to identify new drug targets and to guide the development of therapeutics programs and precision medicine. The RGC is building a human genetic database of millions of sequenced samples linked to rich phenotype data, based on a growing network of collaborations with research organizations around the world. This includes some of the largest sequencing studies in the world, such as the DiscovEHR study in collaboration with Geisinger Health System, and an initiative to sequence 500,000 participants with the UK Biobank. It also includes an expanding set of Mendelian genetics, family based, and founder population genetic studies.

The RGC specializes in translating genetic discoveries into new biology and drug discovery opportunities. Our interests encompass a breadth of different areas across all therapeutic areas and the RGC is highly integrated into all facets of research and development at Regeneron. Program goals include target discovery, indication discovery, derisking, and patient-disease stratification. Objectives include advancing basic science around the world through public sharing of discoveries, providing clinically-valuable insights to physicians and providers of collaborating health-care systems, improving patient outcomes, and identifying novel targets for therapeutic development.

The RGC has 2 Postdoctoral Fellow positions for early career scientist trainees to receive a rigorous scientific training under the auspices of a senior scientist for a training period up to 4-years. Fellows will be expected to conduct creative exploratory research that results in publishable data within their fellowship period and participate in the broader Regeneron Postdoctoral training program." The Postdoctoral Fellowship positions, are Neuroscience and Ophthalmology Therapeutic Area - Req #16309 and Statistical Genomics, Data Sciences and Machine Learning - outlined below.

Fellowship: Statistical Genomics, Data Sciences and Machine Learning
The role will focus on development of new statistical and population genetic methods, theory, computational tools and machine learning, under the supervision of Dr. Goncalo Abecasis or Dr. Jonathan Marchini. Methods development will be motivated by, and applied to, the analysis and interpretation of 100,000s of genotyped and sequenced human subjects. The scale and breadth of the data being collected at the RGC provides opportunities for research on a wide range of topics. We expect that the precise area of research will be decided in collaboration with the successful candidate. Areas of research might include, but are not limited to: analysis of multiple phenotypes, deep learning and machine learning with imaging and genetic data, scalable association analysis, polygenic risk scores, fine-mapping, population structure, Mendelian randomization and graphical modelling, data visualization, summary statistical analysis, family-based association testing, and multi-omics data integration. Continual learning, skills acquisition and research publication will be essential during the role for a productive career at the intersection of human genetics, biology, health and drug development.

The successful candidate will have a strong quantitative research background with a PhD in areas such as Statistical and Population Genetics, Statistical Methods, Machine Learning, Deep Learning or Computer Science; practical experience working with large real-world genetic data sets, developing new methods, statistical computing, and producing high-quality published work. Skills in a range of programming languages suitable for at scale analyses (e.g. C/C++, java, python or R) as well as relevant libraries and frameworks (TensorFlow, Eigen, scikit-learn, MLlib, SQL, jQuery) are required. We expect the candidate to be motivated, creative, communicative and happy to work in a collaborative and inter-disciplinary environment.

How to apply
Candidates should submit a full academic CV together with a short cover letter outlining their motivation for applying to the postdoc program and vision for their future research. Candidates are encouraged to submit at most 1 piece of work i.e. paper, thesis chapter or similar, that is representative of their research to date. Candidates should supply the names of two referees who will be asked to submit reference letters if the candidate is invited to interview.

This is an opportunity to join our select team that is already leading the way in the Pharmaceutical/Biotech industry. Apply today and learn more about Regeneron's unwavering commitment to combining good science & good business.

To all agencies: Please, no phone calls or emails to any employee of Regeneron about this opening. All resumes submitted by search firms/employment agencies to any employee at Regeneron via-email, the internet or in any form and/or method will be deemed the sole property of Regeneron, unless such search firms/employment agencies were engaged by Regeneron for this position and a valid agreement with Regeneron is in place. In the event a candidate who was submitted outside of the Regeneron agency engagement process is hired, no fee or payment of any kind will be paid.

Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability status, protected veteran status, or any other characteristic protected by law.