Match score not available

ARPA-H Computational Biology Advisor (Data Scientist)

Remote:

Full Remote

Contract:

Full time

Salary:

100 - 180K yearly

Experience:

Mid-level (2-5 years)

Work from:

Vatican City, Virginia (USA), United States

Offer summary

Qualifications:

Expert in molecular biology or biophysics, Strong experience with AI/ML in biology, Familiarity with statistical analysis and machine learning.

Key responsabilities:

Implement AI/ML solutions in biological programs
Analyze large datasets like DNA sequencing
Design experiments for biomarker discovery
Integrate data from various sources
Provide scientific support to program teams

ECS Information Technology & Services Large https://ecstech.com/

1001 - 5000 Employees

See more ECS offers

Job description

ECS is seeking a ARPA-H Computational Biology Advisor (Data Scientist) to work in our Remote office. Please Note: This position is contingent upon [contract award].

Job Description

Are you a passionate scientific expert in the field of molecular biology and/or biophysics ready to support R&D initiatives? Are you ready to support the Advanced Research Projects Agency for Health (ARPA-H) in their mission to accelerate better health outcomes for everyone by preparing briefings and reports that can communicate scientific and technical knowledge that inform stakeholders of the high-impact solutions to society's most challenging health problems?

ECS seeks talented and driven Subject Matter Expert (SME) in the field of Molecular Biology & Data Science (e.g., computational biology). In this crucial role, you will serve as a scientific and technical advisor—providing support and thought leadership to the program manager and performer teams responsible for generating R&D solutions for ARPA-H and its focus areas. This role will be supporting the Resilient Systems Office (RSO).

What You Will Do

Serve as Computational Biology Advisor, responsible for implementing AI/ML solutions within biological programs (cellular processes and molecular interactions).
Leverage your knowledge within AI/ML to enable programs and performer teams to analyze massive datasets (e.g., DNA sequencing).
Enable the design of experiments and simulations, particularly as it relates to advanced biomarker discovery techniques to develop biomarkers from patient data.
Support the development of new drug therapies.
Leverage your expert understanding in AI/ML to support the development of new program concepts.
Design and execute computational analyses of large biological datasets generated by techniques such as next-generation sequencing, mass spectrometry, and high-content screening.
Develop and implement novel algorithms and pipelines to extract meaningful biological insights from complex datasets.
Utilize statistical and machine learning approaches to identify patterns, trends, and relationships within the data.
Integrate and analyze data from diverse sources, including public databases and internal datasets.
Collaborate with experimental biologists to design targeted experiments to validate computational predictions.
Stay current with scientific advancements:
Actively track and analyze new research findings in this field.
Identify and propose emerging methodologies and technologies that could enhance the program's progress.
Participate in scientific discussions and presentations, contributing your expertise to the program's overall knowledge base.
Collaborate effectively within a diverse team:
Build strong relationships with computational scientists, engineers, and other scientific advisors involved in the program.
Communicate complex scientific concepts clearly and concisely to both technical and non-technical audiences.
Actively participate in brainstorming sessions and problem-solving exercises to drive the program forward.