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.SummaryWe are seeking a highly motivated individual with a strong foundation in analysis of large multi-omic data sets, computer science concepts and an understanding of molecular / cancer biology. The Institute Research Investigator in Computational Biology will be responsible for deploying innovative computational pipelines, algorithms and dashboard for bulk or single cell next generation DNA sequencing and proteomic data. The successful candidate will conduct data analysis of complex biological experiments and collaborate with experimental scientists to develop novel immunotherapy targets.Education/Qualifications
Master's degree in Bioinformatics, Computational Biology, Data Science, Biostatistics, Computer Scientice, Applied Mathematics or related field.
Proficient coding in one or two computer languages, Python, R, Rust/C.
Experience developing large-scale data analysis pipeline in high-performance environment.
Experience developing large-scale data visualization and management dashboard.
Experience working on bulk or single cell NGS data, and be familiar with popular bioinformatics tools, such as samtools, bwa, GATK, minimap2, STAR, CellRanger, scvi-tools, and Seurat.
Demonstrated knowledge of data science and bioinformatics within a technical discipline (e.g., bioinformatics, statistics, computer science, artificial intelligence, deep learning.)
Preferred Education/Qualifications
PhD degree in related fields .
Practical experience in pipeline engine Snakemake, Nextflow, Cromshell or other equivalent.
Practical experience in working in HPC, or Cloud like AWS, Azure or GCP.
Practical experience in data visualization dashboard framework, R/Shiny, Python/Streamlit or R/Dash.
Practical experience in statistical modeling, machine learning and deep learning using the tools or frameworks,such as TensorFlow, PyTorch, Python/statsmodels, scikit-learn, and other equivalent.
A deep knowledge of statistics and statistical methods applied to complex datasets.
Experience analyzing ATAC-seq and Ribo-Seq data
Experience analyzing proteomics data based on mass spectrometry.
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.CORE COMPETENCIESIC - 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: PhD in related field.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:
Practical experience in pipeline engine Snakemake, Nextflow, Cromshell or other equivalent.
Practical experience in working in HPC, or Cloud like AWS, Azure or GCP.
Practical experience in data visualization dashboard framework, R/Shiny, Python/Streamlit or R/Dash.
Practical experience in statistical modeling, machine learning and deep learning using the tools or frameworks,such as TensorFlow, PyTorch, Python/statsmodels, scikit-learn, and other equivalent.
A deep knowledge of statistics and statistical methods applied to complex datasets.
Experience analyzing ATAC-seq and Ribo-Seq data
Experience analyzing proteomics data based on mass spectrometry.
An understanding of LIMS would be desirable
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.htmlAdditional Information
Requisition ID: 169118
Employment Status: Full-Time
Employee Status: Regular
Work Week: Days
Minimum Salary: US Dollar (USD) 101,325
Midpoint Salary: US Dollar (USD) 127,100
Maximum Salary : US Dollar (USD) 152,000
FLSA: exempt and not eligible for overtime pay
Fund Type: Soft
Work Location: Onsite
Pivotal Position: Yes
Referral Bonus Available?: Yes
Relocation Assistance Available?: Yes
Science Jobs: Yes
#LI-Onsite
Full-time