We seek a talented, energetic, and collaborative bioinformatician to design bioinformatics pipelines and analyze multi-platform data as part of the development of our flagship platform A 3 D 3 a: Adaptive, AI-augmented, Drug Discovery and Development. With expertise in genomics and the design and deployment of bioinformatics tools, the Data Scientist - Bioinformatics will inform our mission to discover novel therapies for cancer patients.

Led by Prof. Bissan Al-Lazikani, Director of Therapeutics Data Science, the intelligent and ever-learning A 3 D 3 a platform is part of the new initiative in Therapeutics Data Science and part of our ambitious Institute for Data Science in Oncology at MD Anderson. A 3 D 3 a will accelerate the discovery and impact of novel therapies for cancer by enabling novel opportunities for optimized therapies for patients with a focus on rare and hard-to-treat cancers through the development of novel machine learning and AI technologies.

Central to this vision, the Data Scientist - Bioinformatics will innovate and deploy bioinformatics approaches to uncover hidden therapeutic opportunities in integrated patient data and will work closely with biologists, data scientists and clinicians.

JOB RESPONSIBILITIES

• Carry out preparation, clean-up, and quality control of biological data, including whole exome sequencing, whole genome sequencing, and RNA sequencing from both bulk and single-cell datasets
• Develop and maintain pipelines for bioinformatics and statistical analyses of aforementioned data types; activities to include handling raw data, evaluating outputs, optimizing parameters and summarizing findings
• Deploy bioinformatics pipelines in high performance computing environments
• Visualize data and interpret results, including implementation of approaches such as variant calling, functional annotation, gene set enrichment, and pathway annotation
• Maintain knowledge of latest bioinformatic approaches and genomic technologies and implement these where appropriate
• Present results at multidisciplinary project meetings
• Produce output for scientific publications and co-author said publications
• Prepare written reports, manuscripts, and grant applications with investigators
• Work closely with the team and collaborators to discover novel therapeutic opportunities for cancer patients

• Deep knowledge of bioinformatics tools and their implementation as part of pipelines, particularly for whole genome sequencing, whole exome sequencing, and RNA sequencing data, in both bulk and single-cell contexts
• Demonstrated experience and understanding of genomic technologies and analysis of data generated
• Analyzing and interpreting outputs to identify insights and hypotheses from data
• Understanding of essential statistical methodologies required for bioinformatics analyses
• Addressing challenges in bioinformatics as well as mitigation strategies including bias, batch correction, etc.
• Applying data clustering (e.g., t-SNE, UMAP, novel approaches) and basic machine learning techniques to complement bioinformatic analyses
• Utilizing High Performance Computing to run large-scale analyses
• Deploying pipelining tools (e.g., Nextflow or similar)
• Unix, R, Python or other scripting/programming languages

EDUCATION:
Required: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.

Preferred: PhD in Natural/Medical sciences or computational biology, ideally with postdoctoral experience

EXPERIENCE:
Required: Three years experience in scientific software development/analysis. With Master's degree, one years experience required. With PhD, no experience required.

Preferred: One year of postdoctoral experience

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