Institute Research Investigator Bioinformatics and Computational Biology

Employer
University of Texas MD Anderson Cancer Center
Location
Houston, Texas
Salary
Competitive
Closing date
Oct 2, 2022

View more

Discipline
Health Sciences
Organization Type
Healthcare/Hospital
Institute Research Investigator: Bioinformatics and Computational Biology

ECLIPSE ( coEvolution of Leukemia and Immunity Post Stem cEll transplant) of Cancer, Leukemia and Immunity Post Stem Cell Transplant) is a novel organization within the Therapeutics Discovery platform at MD Anderson Cancer Center, Houston, Texas, with the mission of making MDACC and its partners recognized leaders in the identification and development of innovative immunooncology therapies that will cure all hematologic malignancies.

Summary

We are seeking an experienced and highly motivated individual with a strong foundation in computer science concepts and an understanding of molecular / cancer biology. The Institute Research Investigator in Bioinformatics and Computational Biology will be responsible for integrating computational modeling with multi-omics experimental data to understand complex biological systems and translate this understanding to the development of oncology therapeutics. These efforts will allow us to advance novel therapeutics currently under development by our Therapeutics Discovery teams and partners.

Key responsibilities
  1. Independently propose innovative solutions to research projects and contribute to project goals through bioinformatics and computational biology data-analysis tools.
  2. Independently design, implement and execute analytical pipelines to target discovery, mechanism of action, and biology of response for targets of interest.
  3. Proactively drive the development and application of cutting-edge tools and methodologies to generate data and propose actionable hypothesis to support functional genomics, cancer biology, and immunotherapy.
  4. Perform common statistical analysis on biological datasets including parametric and non-parametric tests, data mining / machine learning algorithms.
  5. Design, optimize and troubleshoot alternative computational techniques for new biology-based technologies and datasets in order to decipher complex biological systems and enable research team to meet program goals.
  6. Develop and utilize software for interrogation, visualization, and communication of multidimensional datasets to enable hypothesis generation and to gain insight into cancer biology.
  7. Interpret, present and report research findings at internal meetings.


Core Competencies
  • IC - Team with Others:
    • Encourage collaboration and input from all team members;
    • Value the contributions of all team members; and
    • Balance individual and team goals
    • Embrace the ideas of others, nurture innovation and manage innovation to reality
  • IC - Self-Motivation:
    • Set high standards of performance;
    • Pursue goals with energy and persistence; and
    • Drive for results and achievement.
  • IC - Oral Communication:
    • Express ideas clearly and concisely in groups and one-to-one conversations; and
    • Create an environment with open channels of communication.
    • Analytical, organizational and presentation skills
  • IC - Leadership skills
    • Strong results-driven personality with high level of enthusiasm, energy and confidence.
    • Demonstrated excellence and productivity in independent research.
    • Create a learning environment, open to suggestions and experimentation for improvement.


EDUCATION:
Required: Bachelor's degree in biology, biochemistry, molecular biology, cell biology, enzymology, pharmacology, chemistry or related field.

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

EXPERIENCE:
Required: Six years experience of relevant research experience in laboratory With Master's degree, four years of required experience. With a PhD in a natural science or Medical degree, no experience required.

Preferred: With a PhD in bioinformatics or computational biology, no experience is required.

Proficient in a scripting language such as Python, in UNIX, and in statistical computing platforms such as Rstudio. Experience manipulating large datasets and familiarity with high performance computing are essential. Course work in biology (genetics, biochemistry, molecular and cell biology) with an experimental laboratory component. Previous hands-on experience working with computational and statistical tools for the analysis of biological datasets. Specifically, the applicant should have experience with machine-learning and/or data mining algorithms ( i.e. clustering, classification, etc.), and experience utilizing common parametric and non-parametric statistical tests for data analysis. Familiarity with bioinformatics of high throughput DNA sequencing. Development of statistical algorithms, and/or the comprehensive assessment of algorithms, for the analysis of multidimensional datasets. Extensive experience collaborating with bench biologists, with examples where analytical methods enabled the validation of hypothesis.

Experience with experimental design, project planning and working in the context of timelines and deliverables is preferred. Application of relevant expertise in the areas of cancer biology, cell biology, genomics and drug discovery biology to project goals will be valued, especially in the single cell analysis methodologies and techniques. The ability to prioritize and manage multiple experiments in a timely and resource effective manner for enablement of science-based go/no-go decision making is essential. Training in an oncology research laboratory and experience with bench biology techniques. Experience with pathway analysis, network analysis, and transcriptional regulator networks. A knowledge of deep learning neural networks is preferred. A working knowledge of immunology would be useful. An understanding of LIMS is desirable.

The position requires a highly self-motivated individual, with outstanding organizational skills, the ability to effectively present results and conclusions to co-workers, collaborators and manager. Ability to multitask, work well under pressure and drive personal and team objectives that impact critical timelines is expected. A flexible, collaborative attitude is essential for this position.

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