• Develop computational methods to analyze single-cell genomics datasets.
• Document and present the results to lab members and collaborators.
• Interpreting and analyzing biological information derived from genome annotation
• Performing tasks to reduce and consolidate output from software
• Preparing data and reports for utilization by other scientists. 
• Data analysis and interpretation of single-cell functional genomic datasets.
• Data mining and analysis including using various internal resources, and public databases
• Maintaining knowledge of appropriate scientific literature.
• Performing statistical analysis, and comparative analysis.
• Integrate genomic data with external data sources to facilitate the sharing of genomic and proteomic data
• Collecting and curating primary data, and integrating data into a database or a larger project.
• Creating and populating database tables and/or websites.

Skills: Computational Methods, Documentation, Presentation, Biological Information Interpretation, Data Reduction, Reporting, Data Analysis, Data Mining

• Exercising analytical judgment and involving supervisory personnel 
• Execute complex tasks effectively with limited supervision.
• Define and estimate the scope of tasks before implementation.
• Execute projects within estimated time frames.
• Provide project leadership and mentoring beyond the scope of work, including leadership of small ad-hoc project teams.
• Works under direct supervision to execute bioinformatics assignments to meet project goals. 
• Develops and maintains an understanding of the scientific and biological domain supported by the team
• Collaborates closely and effectively with software, bioinformatics, scientific, information technology, and administrative personnel
• Abides by environmental, health and safety policies and procedures. 
• Reporting potential hazards and helping to implement solutions to ensure safety and respect for the environment.
• Strictly adheres to all documented JCVI policies and procedures including carrying out all functions required of Institute employees

Skills: Analytical Judgment, Task Execution, Task Scope Definition, Project Management, Leadership, Bioinformatics, Domain Knowledge, Collaboration

• Extensive expertise in NGS data analysis to analyze RNA-seq, ChIP-seq, ATAC-seq and WGBS datasets generated in the lab for investigation of gene and chromatin regulatory networks in stem cells and cancer.
• Processing and mapping raw NGS RNA-seq, ChIP-seq, ATAC-seq, WGBS, Hi-C and other omics datasets.
• Analyzing RNA-seq, ChIP-seq, ATAC-seq, WGBS, Hi-C, and other omics data sets generated in the lab for investigation of gene and chromatin regulatory networks in stem cells and cancer.
• Download and process published and publicly available omics data sets, and integrate them with datasets generated in the lab 
• Investigate mechanisms of gene regulation in stem cells and cancers.
• Working with the PI, students and postdocs in the lab to analyze omics data sets for the projects.
• Working with collaborators to analyze and process omics data.
• Process data for manuscripts, talks, seminars and grants.
• Learn new pipelines and latest methodologies in the field and apply them to lab research projects.

Skills: NGS Data Analysis, Data Processing, Data Integration, Mechanistic Investigation, Collaborative Analysis, Manuscript, Grant Preparation, Continuous Learning

• Develop and execute scientific collaborations, applying internally developed cancer and immuno-oncology products 
• Detect somatic variants, neoantigens, and tumor escape mechanisms within high-profile and impactful partnerships
• Coordinate with collaborators and internal laboratory operations to transfer and process samples
• Work cross-functionally to translate collaborative findings into actively developed cutting-edge products
• Apply components of innovative cancer and immuno-oncology products
• Novel approaches to neoantigen prediction, TME profiling, and cell-free variant detection
• Develop methods for genomics-based characterization of immuno-modulators and multi-analyte biomarkers for immunotherapy
• Present findings at conferences in the area of cancer and immuno-oncology
• Contribute to the writing of research manuscripts, and prepare figures for scientific papers.
• Arrange and deposit NGS data to appropriate public repositories upon manuscript acceptance/publication
• Developing publicly accessible databases to share Stitzel Lab data and results with the islet biology and biomedical research communities

Skills: Scientific Collaboration, Genomic Analysis, Sample Transfer, Communication, Product Application, Bioinformatics, Method Development, Presentation

• Develop and maintain computational tools for epigenomic analyses, including Fiber-seq, DNaseI-seq, ChIP-seq, DNA methylation, and RNA-seq.
• Identifying genetic variants using next-generation and single-molecule real-time (SMRT) long-read sequencing.
• Graphical visualization of data and integration of diverse epigenomic and genomic datasets.
• Basic scientific skills, including the ability to keep detailed records of computational tools and analyses.
• Develop and maintain an organizational system for sequencing data.
• Provide status reports to the Principal Investigator on the status of projects.
• Present analysis findings at group meetings and national conferences
• Document approaches and processes clearly and comprehensively
• Process, visualize, and analyze epigenome (ChIP-seq, ATAC-seq), transcriptome (RNA-seq), and single-cell (scRNA-seq, snATAC-seq), next-generation sequencing (NGS) data
• Implement and run pipelines and software packages for differential epigenome/transcriptome, single-cell, and allelic analyses

Skills: Computational Tool, NGS Analysis, Data Visualization, Scientific Record, Data Management, Reporting, Presentation, Documentation

• Understand the principles of molecular simulations and the interpretation of results. 
• Independently provides troubleshooting for data generation and processing. 
• Implements triaging and generates reports.
• Develops, implements, and refines bioinformatic workflows and tools for analyzing and visualizing molecular simulation data. 
• Runs standardized workflow for annotating protein structures with genomics data.
• Leads the analysis and writing for a portfolio of modeling projects and methods development. Contributes to collaborative research publications. 
• Presents regular project updates at meetings with collaborators.
• Maintains a working understanding of principles in genetics, biochemistry, molecular biology, and biophysics, in support of #1. 
• This position is about genomics interpretation, not basic sciences.
• Adapts bioinformatics tools, visualization packages, and annotation resources 
• Perform research analysis independently and accurately flexibility and competency in data wrangling.
• Develop the automated analysis methods to assess the model quality and computed features
• Assess the analysis of MD simulations statistical mechanics and machine learning

Skills: Molecular Simulation, Data Troubleshooting, Reporting, Bioinformatic Workflow, Protein Structure Annotation, Project Leadership, Collaboration, Communication

• Working experience in Bioinformatics, Statistics, Computational Biology, or related fields.
• Experience in a professional research environment programming with R and Python
• Experience in a professional research environment managing and analyzing NGS datasets.
• Working knowledge of public biological databases (NCBI, ENCODE, ENSEMBL, TCGA, UCSC, etc.).
• Excellent programming skills such as R, Python, and Unix/Linux.
• Team-oriented with excellent written and verbal communication skills.
• Experience working in NGS and functional genomics data analysis
• Solid knowledge of molecular biology as it relates to DNA sequences, sequencing technologies, and genomics.
• Strong written and verbal communication skills, and organizational skills.
• Excellent organization and time management skills and ability to meet schedules.
• Ability to collaborate across a multi-disciplinary team, and work independently.

Qualifications: BS in Bioinformatics with 3 years of experience

• Experience evaluating and comparing different computational pipelines for alignment, variant calling, and functional annotation
• Experience in processing high-throughput biomedical data (data cleaning, normalization, analysis, interpretation and visualization)
• Ability to understand and analyze data from complex experimental designs
• Proficiency in at least two of the following programming languages (Python, R, Perl, Java and C/C++)
• Working experience in bioinformatics, computational or systems biology, physical or computer science 
• Directly related experience in a professional research environment
• Experience working in a Linux HPCC with NGS applications in a professional research environment
• Mastery of the principles of experimental design and modern data analysis paradigms.
• Strong interpersonal skills with the ability to work independently.
• Excellent organizational and time management skills.

Qualifications: BS in Computational Biology with 5 years of experience

• Experience working in computer science, Math, Biomedical Science, or a related field
• Demonstrated ability to understand and develop literature mining algorithms
• Knowledge of literature mining complexities in determining genotype/phenotype correlations
• Understanding of bioinformatics concepts and introductory programming skills
• Ability to self-direct with little or abstract day-to-day instruction
• Excellent written and verbal communication skills
• The ability to document and communicate complex scientific concepts for a variety of audiences
• Must be able to obtain and maintain a security clearance
• Experience with developing context-based literature mining algorithms
• Knowledge of Next Gen Sequencing and methods to determine rare variants
• Experience working with web and database technologies.

Qualifications: BS in Computer Science with 2 years of experience

• Commitment to solving biological problems and communicating these solutions
• Experience working in submitting data sets to public repositories
• Ability to manage large genomic data sets including integration with data available from public sources
• Experience in designing and creating bioinformatics pipelines for cancer genomics
• Experience in creating and optimizing computational frameworks for clinical genomics
• Understanding and experience with multiple bioinformatics options and setups for clinical genomics
• Understanding and experience in creating platforms for pathologists to sign out of genomic data
• Experience in creating clinical-grade databases for gene annotation for cancer on a large scale
• Experience in Exome sequencing, metagenomics, ChIPSeq, RNASeq, DHS-Seq, microarray analysis, DNA methylation analysis
• Familiarity with public databases such as NCBI, Ensembl, TCGA, cBioPortal, Broad FireHose
• Knowledge of or experience working in a cluster environment

Qualifications: BS in Genetics with 4 years of experience

• Working experience in bioinformatics or biological sciences.
• Excellent communication and presentation skills
• The ability to work across functional teams and with non-experts.
• Expertise in next-generation sequencing data generation and processing from raw reads to biological insight.
• Experience in experimental data analysis, statistical methods, and visualization.
• Knowledge of genomics (cancer) and relevant computational tools.
• Proficiency in the Python programming language, as well as working on distributed high-performance computing Linux environments.
• Ability to make a difference in a fast-paced startup environment.
• Knowledge of the fundamentals of microbiome biology, including both the considerations for in vitro and in vivo studies, normalization, and contamination detection.

Qualifications: BS in Biostatistics with 6 years of experience

• Knowledge of statistical and data mining techniques such as PCA, hierarchical clustering, ANOVA, SVM, PLS, and LIMMA.
• Experience with R or other open-source software packages for biological and statistical data analysis.
• Advanced skills in a high-level programming language, preferably Python, or R.
• Experience with genomics software packages, QIIME, or related packages.
• Programming experience, in a high-performance computing setting.
• Familiarity with statistical learning techniques, from regression to machine learning.
• Experience with architecture and tools for managing large datasets (especially “omics” data)
• Excellent communication, analytical and organizational skills, both written and verbal.
• Ability to work independently and as part of a team while being collaborative in resolving problems.
• Excellent organizational skills, problem-solving skills, and attention to detail.
• Excellent oral and written communication skills.

Qualifications: BA in Applied Mathematics with 1 year of experience