MD Anderson Cancer Center Institute Research Investigator: Computational Biology, ECLIPSE in Houston, Texas
ECLIPSE (Evolution 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. Please see the website for further details:
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 Computational Biology will be responsible for integrating computational modeling with quantitative 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.
1.Independently propose innovative solutions to research projects and contribute to project goals through computational biology data-analysis tools.
2.Independently design, implement and execute analytical pipelines to inform on target discovery, target biology, 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.
Required: Bachelor's degree in biology, biochemistry, molecular biology, cell biology, enzymology, pharmacology, chemistry or related field.
Preferred: Required: 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.
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.
Proficient in a scripting language such as Python, in UNIX, and in statistical computing platforms (R, Matlab, etc). 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 (i.e. t-test, ANOVA, Wilcoxon- signed-rank test, Fisher's exact test, etc.) for data analysis. Familiarity with appropriate data normalization techniques and analysis of batch effects. 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. The ability to plan, execute and interpret experimental data in a timely fashion is essential. 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. Previous experience with next-generation sequencing analytics (alignment tools, mutational variant callers, ChIP-seq, etc). Experience with pathway analysis, network analysis, and transcriptional regulator networks. An understanding of LIMS would be 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.
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
Requisition ID: 134879
Employment Status: Full-Time
Employee Status: Regular
FLSA: non-exempt, eligible for overtime, and is subject to the provisions of the Fair Labor Standards Act (FLSA)
Work Week: Days
Fund Type: Hard
Pivotal Position: No
Minimum Salary: US Dollar (USD) 85,000
Midpoint Salary: US Dollar (USD) 106,250
Maximum Salary : US Dollar (USD) 127,500
Science Jobs: No