Institute Senior Research Scientist - Data Science

The University of Texas MD Anderson Cancer Center aims to eliminate cancer in Texas, the nation, and the world, through outstanding programs that integrate patient care, research, and prevention, and through education for undergraduate and graduate students, trainees, professionals, employees, and the public.

MD Anderson Therapeutics Discovery Division
Within The University of Texas MD Anderson Cancer Center lies the Therapeutics Discovery Division (TDD), a powerful engine driving the future of new targeted, immune- and cell-based therapies. Therapeutics Discovery eliminates the bottlenecks that hamper traditional drug discovery by employing a multidisciplinary team of dedicated researchers, doctors, drug developers, and scientific experts working together to develop small-molecule drugs, biologics, and cellular therapies. Our unique structure and collaborative approach allow the team to work with agility, bringing novel medicines from concept to clinic quickly and efficiently - all under the same roof.

The TRACTION platform
The Translational Research to AdvanCe Therapeutics and Innovation in ONcology (TRACTION) platform is an industrialized translational research group that aligns world-class drug discovery and development with highly innovative the science and clinical care research, for which MD Anderson Cancer Center is known. Through an investment in patient-centric research, we have developed the infrastructure, platforms, and capabilities to enable transformative research. TRACTION's approach combines innovative cancer genetics, disruptive technologies, deep mechanistic biology, disease modeling, and pharmacology to accelerate the translation of novel discoveries into definitive clinical hypotheses. By partnering with the drug discovery engines within Therapeutics Discovery, we aim to advance a portfolio of small molecules, biologics, and cell therapies for our patients. We work in a fast-paced, milestone-driven environment with a focus on team science and interdisciplinary research. Our unique approach has created a biotech-like engine within the walls of the nation's leading cancer center to bring life-saving medicines to our patients more quickly and effectively.

We are seeking an accomplished, energetic, and collaborative scientist to join our team as a Senior Research Scientist of Computational Biology. With extensive computational biology experience in a drug development environment, the Institute Senior Research Scientist (SRS) will lead data integration efforts to identify genes/pathways pertinent to tumor development and treatment. The ideal candidate will coordinate the application and development of cutting-edge tools and methodologies to enable advancement of Institute projects through leadership and analytical activities. In addition, the SRS will interface more broadly with MD Anderson data science projects, and our corporate partner's computational biology teams, to develop innovative data-driven translational strategies that advance projects to critical inflection points. Success will be measured by the ability to execute and lead the computational biology efforts within a highly collaborative, team-science environment to enable hypothesis-driven testing of oncology therapeutics and/or biomarker strategies in the clinical setting. Overall, the deep biological insights elucidated by the SRS and will have a rapid and direct impact on patient care.

Key Functions

1. Apply expert knowledge of computational biology in areas such as oncogenomics, network biology, regulatory genomics, immune-oncology, single cell sequencing, and/or data integration to enable progression of innovative drug candidates into the clinic.
2. Leverage patient-centric-omic databases to enable translational biology hypothesis generation and design studies for validation in clinically relevant contexts.
3. Perform statistical analysis on biological datasets including parametric and non-parametric tests, data mining / machine learning algorithms and document steps in computational notebooks.
4. Work with Computational Biology scientists to identify or develop novel analytical strategies to inform on target discovery, target biology, mechanism of action, and biology of response for targets of interest.
5. Collaborate with internal biologist, external data scientist, and clinical teams, to facilitate data-driven program decisions.
6. Mentor Computational Biology scientists and interns.
7. Interpret, present, and report research findings at internal meetings and external scientific conferences.
8. Use independent thinking and leadership skills to manage resources and personnel.
9. Work well under pressure and drive projects that impact critical timelines.

Education

Required: Master's degree in Biology, Biochemistry, molecular biology, cell biology, enzymology, pharmacology, chemistry or related field. Education preferred: PhD in one of the natural sciences or related field or Medical degree.

Preferred: Ph.D. in Computer Science, Engineering, Applied Mathematics, Biostatistics or a related discipline from an accredited university.

Experience

Required: Eight years experience of relevant research experience in lab. With preferred degree, three years of required experience.

Preferred Candidate will possess the following:

1. MD or PhD with >3 years of relevant post-degree experience in a pharmaceutical/biotech environment.
2. Strong data analysis skills, ability to interpret results, design of follow-up experiments, troubleshoot issues with analytical methods, and effectively present results and conclusions to co-workers, collaborators and senior leadership.
3. Extensive knowledge and experience in areas of computational biology including, but not limited to, oncogenomics, systems biology, network biology, regulator genomics, single cell sequencing, machine learning, as evidenced by publication in peer-reviewed journals.
4. Experience working with cross-functional drug discovery teams to drive critical inflection points.
5. Expertise in programing languages (Python, R), scripting languages (bash), high-performance computing, code version control, and computational notebook tools.
6. Experience with cloud computing, container images, reproducible workflows, and interactive visualization.
7. Experience working with high-dimensional molecular profiling techniques to understand complex biological systems and translate this understanding to the development of therapeutics
8. Evidence of utilization of cancer genomics to inform on clinical positioning of development drug candidates.
9. Evidence of independent thinking and leadership skills.
10. Evidence of mentoring and managing PhD scientists is a plus.

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html