The primary purpose of the Associate Data Scientist is to work as a computational scientist in the laboratory of Dr Kunal Rai, in Genomic Medicine Department at The University of Texas MD Anderson Cancer Center, Houston, Texas. The position is focused on discovery of cancer-driving epigenome-networks by applying computational methods for the analysis of single cell multiome and spatial transcriptomics and epigenomics (ATAC-Seq/CUT&Tag) datasets and integrate with complex high-dimensional omics datasets from tumor samples in different cancer types/malignancies. This position will also collaborate with a group of wet lab and computational scientists to derive novel biological insights and identify biomarkers and therapies.
Rai laboratory is situated in a highly dynamic and stimulatory environment for learning. MD Anderson Cancer Center is a top-rated hospital in cancer care in the United States. The institute offers active graduate and postdoctoral training programs and the unmatched scientific environment of the Texas Medical Center, the world's largest biomedical center.
JOB SPECIFIC COMPETENCIES
* Carry out preparation, clean-up, and quality control of biological data, including scRNA-Seq, scATAC-Seq, Spatial transcriptomics and/or other multi-dimensional omic data modalities,
* 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.
* Collaborate with interdisciplinary teams to design experiments and analyze data from various single cell platforms.
* Maintain knowledge of latest bioinformatic approaches and variety sequencing technologies, especially in single-cell context.
* 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.
Expected Skills
* Deep knowledge of bioinformatics tools and their implementation as part of pipelines, particularly for scRNA-Seq, scATAC-Seq, Spatial transcriptomics and/or other multi-dimensional omic data modalities.
* 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 such as bias, batch correction, etc.
* Utilizing High Performance Computing to run large-scale analyses.
* Unix, R, Python, or other scripting/programming languages.
Other duties as assigned.
Working Conditions
Laboratory environment
This position requires:
Working in Office Environment
____No
__X_ Yes
Working in Patient Care Unit (e.g., Nursing unit; outpatient clinic)
_X_ No
____Yes
Exposure to human/animal blood, body fluids, or tissues
__X__No
__ Yes
Exposure to harmful chemicals
__X__No
___ Yes
Exposure to radiation
_X_ No
____ Yes
Physical Demands
Indicate the time required to do each of the following physical demands:
Time Spent
Never
0%
Occasionally
1-33%
Frequently
34-66%
Continuously
67-100%
Standing
X
Walking
X
Sitting
X
Reaching
X
Lifting/Carrying
Up to 10 lbs.
X
10lbs to 50 lbs.
X
More than 50 lbs.
X
Pushing/Pulling
Up to 10 lbs.
X
10lbs to 50 lbs.
X
More than 50 lbs.
X
Use computer/keyboard
X
EDUCATION: Required: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field.
Preferred: PhD in natural/biological science, computational, bioinformatics.
EXPERIENCE: Required: Two years experience in scientific software or industry development/analysis.
Preferred: Computational biology experience (at least 1 or 2 projects) working in a lab or industry. Experience with R and Python. Experience with Machine learning/Deep learning OR single cell data OR spatial data analysis. Experience with Spatial transcriptomics data analysis. Experience with Epigenomics (ChIP-Seq, RNA-Seq, CUT&Tag, Hi-C) data analysis. At least 1 paper in bioinformatics/comp biology.
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
