Assistant Data Scientist

1 week ago

Houston, Texas, United States MD Anderson Cancer Center Full time

The Department of Epigenetics and Molecular Carcinogenesis is an interdisciplinary, basic science research department that conducts groundbreaking research aimed at defining the mechanisms controlling normal cell growth, proliferation, differentiation, and survival as well as mechanisms controlling genome maintenance to identify the aberrations in these processes that drive cancer.


Epigenetics and Molecular Carcinogenesis
Epigenetic gene regulation is important for both normal development and disease states.

In cancers, aberrant promoter CpG island hypermethylation correlates highly with gene inactivation and can account for lack of gene expression where mutations do not exist.

Dr.

Ting is interested in dissecting the mechanisms of epigenetic gene silencing and understanding the functional relevance of DNA methylation in diseases.

Dr.

Ting's lab has three major focus areas:
-
Pioneering technical and computational tools for genome-wide DNA methylation assay. Dr. Ting developed MBD-isolated Genome Sequencing (MiGS), which is a cost-effective technique to survey whole genome DNA methylation patterns. The Ting lab also develops computational tools that facilitate sequencing data analyses and interpretation.
-
Defining novel and clinically relevant functions for DNA methylation. We have defined genome-wide abnormal DNA methylation patternsin colon, bladder, and prostate cancers. Knowing where these disruptions occur enabled us to generate and test hypotheses regarding the function of these changes. We investigate both gene promoters and non-promoter regions with the goal of defining context-specific functions of DNA methylation.
-
Delineating the mechanics of DNA methylation in cancer. Wide-spread disruptions to DNA methylation patterns are contribute to tumorigenesis and progression, but the regulatory mechanisms that establish, maintain, and modify these patterns are still being worked out. Researchers in Dr. Ting's lab explore the roles for epigenetic enzymes, small non-coding RNAs, and environmental exposures in the initiation and maintenance of abnormal DNA methylation patterns in cancer.

Please note this role is Hybrid Onsite/Remote. Some job duties can be fulfilled partially remotely but may require some time spent onsite - typically one to two days per week.

KEY FUNCTIONS

Sequencing Data Analysis

  • Assist with writing computer codes to establish new computational pipelines using R, Python, and C++.
  • Create new scripts as directed to carry out specific data manipulation or adapt published software to project needs and computational infrastructure.
  • With supervision and assistance from senior bioinformatics personnel and PI, perform genomic data analyses, such as single cell RNAseq, RNAseq, ChIPseq, and HiCseq.
  • Provide assistance and input in developing and implementing workflow for data analysis in collaboration with research scientists. Assist with hypothesis testing.

Data and Systems Maintenance

  • Under direct supervision, build and deploy data analysis support systems for large data sets.
  • Interact closely with systems administrator to provide assistance for maintaining and running software packages for next generation sequencing data analyses.
  • With supervision and assistance from senior bioinformatics personnel and PI, conduct data QC, sequence alignment, sequence analyses, annotation, and interpretation.
  • Organize and present findings.

Research Support

  • Contributes to the development of procedures and makes recommendations on new procedures.
  • Explore and learn new technologies relevant to lab research projects.
  • Interact closely with PIs and assist with other research, computational, scientific or support staff to accomplish project focus or results.

EDUCATION

Required:

Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Statistics, Computer Science, Computational Biology, or related field.


EXPERIENCE

Required:
None

Preferred:
Experience in genomic data analyses, such as single cell RNA-seq, RNA-seq, ChIP-seq, and HiC-seq.

Additional Information

  • Requisition ID: 168294
  • Employment Status: Full-Time
  • Employee Status: Regular
  • Work Week: Days
  • Minimum Salary: US Dollar (USD) 66,000
  • Midpoint Salary: US Dollar (USD) 82,500
  • Maximum Salary : US Dollar (USD) 99,000
  • FLSA: exempt and not eligible for overtime pay
  • Fund Type: Soft
  • Work Location: Hybrid Onsite/Remote
  • Pivotal Position: Yes
  • Referral Bonus Available?: No
  • Relocation Assistance Available?: Yes
  • Science Jobs: Yes
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