The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University is recruiting an individual to lead analyses on epigenomics analyses such as (ChIP-seq, ATAC-seq and RNA-seq) and single cell analyses in cancer models. This person will be active in the data pre-processing stages as well as analysis and interpretation of results.
The Toska lab integrates biochemistry, cell signaling, genomics and epigenomics at bulk and single cell level to study the fundamental processes by which epigenetic regulators regulate transcription, have the ability to drive tumorigenesis and dictate therapeutic response in breast cancer. The Fertig lab develops time course models of therapeutic resistance and performs single cell technology development. Her computational methods are used to determine the molecular mechanisms of therapeutic resistance from multi-platform genomics and epigenomics data. The successful candidate will become a fundamental component of this multidisciplinary team with mentorship in both computational and biological processes affecting therapeutic response in cancer.
Eligible candidate will be involved in designing and developing analysis plans to address biological hypotheses in our ChIP-seq/ATAC-seq/RNA-seq and RNA-seq and ATAC-seq at the single level acquired from breast cancer models such as cell lines, organoids, and patients treated with targeted therapies. The candidate will interact daily with other data analysts within the Institute, as well as Genomics experts, and clinicians. This position requires collaboration with clinical and scientific investigators in research/study design, data analysis plans, algorithm development, grant applications, and preparation of presentations and publications. The candidate should work independently and in collaboration with faculty to solve problems posed by the clinical and laboratory investigators along the study design, data generation, collection and management process; interaction with bioinformatic experts, biostatistician program developers, computational scientists, health informatic experts as well as postdoc fellows from the Sidney Kimmel Comprehensive Cancer Center and the Bloomberg School of Public Health on our epigenomic data mining initiatives with the goal of translating these findings into therapeutic modalities for cancer patients. The applicant may share efforts between 1-3 labs.
Specific Duties & Responsibilities
Plan data management including determining type, format of data and types of documentation, considering privacy, confidentiality and other ethical issues
Facilitate acquisition of single cell sequencing data from core facilities
Clean data by coding missing data, fixing or deleting miscoded data, transforming variables into more useful formats, and annotating the data in proper way, use descriptive statistics to help characterize and summarize the data
Collaborate with clinical and scientific investigators in the breast cancer and biostat teams to propose ideas for new projects, design research, develop data plan, and prepare analyses with general direction from investigators
Apply different technical approaches to visualize the data and prepare publication-quality tables and graphs based on valid analysis
Lead or participate actively in the team responsible for designing and validating analysis data sets, programs, and statistical output products
Identify potential data problems from analytic queries and bring them to the attention of the team
Demonstrate understanding of high dimensional data collection processes and data sets and share knowledge with collaborators
Collaborate closely with investigators, and other team leadership to ensure that research study or project results and conclusions are presented accurately and without bias
Demonstrate progress in ability to multi-task and manage time spent working with individual faculty members and on specific projects
Participates in regularly schedule meetings with study investigators and team. Prepares progress reports as needed. Maintain appropriate systems for data organization
Assure data quality for documentation and dissemination of data. Conduct and track specific activities to accomplish project goals, including evaluating and reporting data and documenting analytic procedures
Able to work collaboratively in a team environment with a high degree of initiative and self-motivation
Equipment, Machine, or Tool Requirements:
Experience with computers and servers and knowledge of Linux/UNIX as well as other common operating systems such as Mac OS and Windows is necessary
Experience with server configuration and troubleshooting preferred
Ability to use the internet and web-based scholarly search engines
Bachelor's Degree in Statistics, Computer Science Bioinformatics or related field
Minimum of 3 years related experience in analyzing genomic data
Experience with code development, optimization, and testing
Additional education (Master's level) may substitute for required experience, to the extent permitted by the JHU equivalency formula:
* JHU Equivalency Formula: 18 graduate degree credits may substitute for one year of experience. For jobs where equivalency is permitted, up to two years of non-related college course work may be applied towards the total minimum education/experience required for the respective job. *
Master's Degree in Statistics, Computer Science Bioinformatics or related field
Familiarity with cancer epigenetics
Familiarity with common computational biology tools and software packages, such as Bioconductor
Special Knowledge, Skills, and Abilities
Proficiency with bioinformatics concepts, methods, and tools, with experience working in languages such as R or Python, leveraging Bioconductor and bioconda
Coursework or work experience covering topics in statistics, molecular biology, genetics, and script-level programming
Proficiency with genomic data, tools, and databases
Familiarity with common computational biology tools
Experience with experimental design principles, reproducible research principles, and data storage, security, and safety
Excellent interpersonal skills in consulting with researchers and understanding their problems
Excellent writing and verbal skills in the preparation and presentation of reports
Excellent organizational skills and attention to details are required
Must be detail-oriented, focused, creative, and independent
Proficiency in both written and spoken English with excellent communication skills
Classified Title: Research Data Analyst Working Title: Research Data Analyst Role/Level/Range: ACRP/04/MC Starting Salary Range: $45,195 - $62,225; Commensurate with Experience Employee group: Full Time Schedule: Monday-Friday, 8:30am- 5:00pm, Up to 37.5 hrs/week Exempt Status: Exempt Location: 04-MD:School of Medicine Campus Department name: 10002942-SOM Onc Breast and Ovarian Cancer Personnel area: School of Medicine
The successful candidate(s) for this position will be subject to a pre-employment background check.
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