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Data Scientist Genomic Medicine
The Wang Laboratory at MD Anderson Cancer Center is a computational biology research lab. We apply innovative bioinformatics approaches to deeply profile tumor cells and cells of the tumor microenvironment to identify tumor cell-intrinsic and microenvironmental factors driving tumor phenotypic heterogeneity and evolution, and better understand the mechanisms underlying early tumorigenesis, disease progression, and the development of therapy resistance.
JOB SPECIFIC COMPETENCIES
* Benchmark and select computational analysis for bulk, single-cell, and spatial transcriptomics analysis.
* Develop computational methods as needed for integrative analysis of single-cell and spatial multiomics data.
Collaboration and Communication:
* Work with teams of individuals to integrate data/metadata and assist postdocs and students in the lab in analyzing and resolving analysis issues as needed.
* Assist with manuscript and grant preparation and present results during lab meetings, department, and institutional meetings and seminars, and appropriate scientific conferences.
Other Duties:
* Attend collaborator meetings and team working group meetings. Prioritize and manage multiple projects in a timely and resource-effective manner.
* Read literature, gather relevant information systematically, and confer with the supervisor regarding new procedures.
With Drive, you see that you can serve as a leader whether you have a formal leadership role or not. You tackle problems, move past setbacks and hardships, and don’t lose sight of your goals. (Competencies: Self-Confidence, Analytical Thinking, Innovative Thinking, Technical Expertise)
You demonstrate Professionalism by setting the example for others and consistently modeling MD Anderson’s values and service standards. You communicate effectively in a variety of ways. (Competencies: Inspire Trust, Oral Communication, Written Communication)
Through Emotional Intelligence, you maintain awareness of your own emotions and the emotions of those around you. Use nonverbal cues and feelings to engage others in an inclusive and responsive way. (Competencies: Active Listening, Teaming, Self-Reflection)
Having Coachability means you are engaged in relentless learning. You constantly ask questions and stay curious. You understand that the organization constantly evolves, and you should as well. (Competencies: Develop Oneself, Adaptability)
Onsite Presence:
Soft Skills
* Must be honest, highly motivated, reliable, responsible, and well-organized.
* Strong attention to detail, multi-tasking ability, and a willingness to learn new technologies.
* Excellent written and verbal communication skills.
* Ability to work well in a collaborative and interdisciplinary team environment (strong plus).
WORKING CONDITIONS
|
Frequency |
Deadlines |
-- |
|
Frequency |
Weight |
Sitting |
Constant 67-100% |
-- |
Analytical Ability |
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: Master's or Ph.D. degree in computer science, quantitative science, bioinformatics, biostatistics, or a related field.
EXPERIENCE:
Required: Three years experience in scientific software or industry development/analysis. With Master's degree, one years experience required. With PhD, no experience required.
Preferred:
* Experience with best practices in single-cell analysis, including multimodal data integration (scTCR/BCR sequencing, and spatial transcriptomics).
* Demonstrated ability to develop, optimize, and maintain bioinformatics pipelines.
* Proficiency in at least one programming language such as R or Python (experience with Perl and/or C/C++ is a plus).
* Expertise with modern workflow languages, such as Nextflow, WDL, and CWL.
* Experience with containerization technologies, including Docker, Docker Swarm, and Kubernetes.
* Experience with version control systems (Git, and GitHub) and Linux administration.
* Familiarity with FAIR (Findable, Accessible, Interoperable, and Reusable) principles for data and tool development.
* Knowledge of high-performance computing environments are a plus.