• Become an integral member of target and drug discovery teams, helping to move programs from concept to the clinic
• Help design, build and implement computational methods and processes to integrate data and findings from genetics and functional genomics experiments
• Work with the Human Genetics, Functional Genomics and Stem Cell departments to implement production-quality, cutting-edge data management, analysis and visualization tools
• Help build production-quality, scalable bioinformatics and genetics pipelines and take responsibility for managing and integrating functional genomics and human genetics data
• Build and maintain relationships with external collaborators to obtain and manage complex genetics data
• Communicate data and scientific results to both internal and external audiences and contribute to open-source and collaborative projects
• Ensure the maintenance of multiple proprietary platforms.
• Lead the statistical analysis of different types of biological, structural and molecular data.
• Generate machine-learning models based on structural and chemical protein descriptors.
• Develop innovative technologies to optimize proteins for the manufacturing processes and support biotherapeutics/vaccines R&D.
• Participation and collaborative development with both internal and external groups researching rare genetic diseases, cancer and population genetics.

Skills: Bioinformatics Pipeline Development, Data Integration, Statistical Analysis, Machine Learning Model Development, Data Management and Visualization, Collaborative Research, Protein Optimization, Scientific Communication

• Analyze next-generation high-throughput DNA sequencing data ranging from single research experiments to very large data sets
• Develop tools and automated analysis pipelines for bioinformatics analyses, and diagnostic tests, including variant detection and quality control
• Design new algorithms, methods and tools for DNA sequencing data analysis and propose improvements to the existing research infrastructure
• Produce high-quality written documentation including study plans and reports
• Produce correct conclusions based on rigorous mathematical analysis and principles of statistics and probability
• Collaborate effectively with R&D, production, and clinical teams to build efficient workflows
• Be the "go-to" person for bioinformatics and related issues
• Ensure internal processes and metrics are aligned to create the highest product quality and competitive advantage
• Develop Python software infrastructure to support algorithm testing and simulation studies
• Produce clear, concise and correct technical documentation including research reports and algorithm specifications
• Responsible for leading the computational biology effort and build it from the ground up.

Skills: DNA Sequencing Data Analysis, Bioinformatics Pipeline Development, Algorithm Design, Mathematical Analysis, Workflow Optimization, Python Software Development, Technical Documentation, Computational Biology Leadership

• Support scientists by assessing their bioinformatics needs and defining proper informatics solution(s)
• Assist in all phases of analysis from data processing and quality control through final analytical results
• Prepare sequencing analysis and complete reporting to facilitate analysis
• Assist with working with computational tools for the exploration of high-dimensionality datasets and test statistical models
• Work with researchers to translate these models and analyze data from experiments
• Help develop toolsets and bioinformatics applications that embed analysis methodologies to internal and external collaborator
• Train in the analysis of biomedical research data using descriptive statistics and inference tests
• Train and work in statistical programming using R-script.
• Analyze and interpret data such as gene expression, SNPs, NGS (RNA-Seq, WES/WGS), proteomic data, and clinical metadata from both a biological and clinical perspective
• Apply computational biology methodology and bioinformatics knowledge to existing bioinformatics platforms
• Applying knowledge of variant calling tools such as SAMTools, GATK, BWA or similar

Skills: Bioinformatics Solutions, Data Processing, Statistical Model Testing, Toolset Development, Biomedical Data Analysis, R Programming, Variant Calling, Computational Biology

• Interact closely with functional teams to extract value from existing data or new experiments
• Act as advisor to cross-functional teams on statistics, machine learning, data manipulation and other aspects of data science
• Drive continual improvement of modeling techniques with high impact and interpretability
• Contribute to the design of experiments and steering of lab technologies compatible with model development
• Learn aggressively and strive to stay at the forefront of data science and scientific advances
• Work in a highly collaborative environment to develop analysis methods that aim to solve complex computational research problems
• Using internal and publicly available datasets, work collaboratively within scientific and clinical projects to identify biomarkers for patient stratification and indication selection.
• Support preclinical- and discovery-stage projects by translating scientific questions into hypotheses that can be addressed using computational workflows, data visualizations, and statistical testing.
• Effectively communicate data analysis processes, results, and additional deliverables to internal project teams.
• Design and implement interactive webpage for data visualization and promote data accessibility
• Interpret the data and communicate the findings

Skills: Data Science Consulting, Machine Learning, Experimental Design, Computational Research, Biomarker Identification, Data Visualization, Statistical Analysis, Collaborative Problem Solving

• Computational analysis of human genetics, genomics, and transcriptomics data
• Characterization of relevant model systems through analysis of RNA-seq, WGS, Epigenetics, and Single Cell data
• Implementing comparative genomics approaches to translate findings between humans and model systems, and across model systems
• Documentation of analysis tools, methods, and results through adaptation of reproducible research best practices
• Presentation of findings and scientific data in written and oral formats
• Collaborating with other scientific teams within the company
• Lead genomic analysis for gene editing quantification and profiling across therapeutic programs
• Explore, develop, document and maintain tailored algorithms/analysis methods for both short-read sequencing and long-read sequencing data (ONT and PacBio)
• Design and implement computational biology pipelines and algorithms. Collaborate with bioinformatics engineers to support internal efforts and research activities
• Adapt, innovate, and refine existing genome engineering methods for projects that help support the Research platform and customer product development goals.
• Stay current on advances in the genome engineering field, attend virtual and in-person conferences and present relevant findings during internal and external forums.

Skills: Human Genetics Analysis, RNA-seq Data Analysis, Comparative Genomics, Reproducible Research, Scientific Communication, Genomic Analysis, Algorithm Development, Computational Biology Pipelines

• Advising junior-level scientists
• Hypothesize on any discrepancies and recommend changes to protocols
• Develop and deliver educational courses on machine learning techniques on classification regression models and reinforcement learning
• Collaborate with the Data Science Team to use the neuroimaging and phenotypic data collected by them and support the quantification of the data
• Lead software engineering efforts to package new or existing machine learning methods into open-source code usable by NIMH or external researchers
• Provide consulting and support activities to NIMH researchers employing statistical and machine learning techniques
• Author research papers, in collaboration with the Team and NIMH researchers, on the Teams results from development and support activities
• First-author research papers about novel techniques devised by the contractor
• Apply existing machine learning methods, eg, classification and regression models, deep learning, and decision forests, to help answer questions posed by researchers
• Develop new machine learning techniques in response to NIMH researcher needs, including statistical modeling of complex neural imaging and behavioral data collected in internal experiments
• Evaluate new technologies and methods that enhance the capabilities, activity, and specificity of the genome engineering toolbox.
• Lead genomics activities for internal R&D efforts providing bioinformatics support, designing genome-scale experiments, and analyzing NGS data.

Skills: Machine Learning, Statistical Modeling, Neuroimaging Data Analysis, Software Engineering, Bioinformatics Support, Educational Course Development, Genomics Research, Research Collaboration

• Take a leading role in the integration of insights from genetic and genomic data to support the identification of new drug targets, the review of proposed targets, the ongoing validation of existing targets, and the identification of potential patient selection biomarkers
• Provide hands-on support to build out DF genetics and genomics databases
• Develop analytics for common genetic and genomic data use cases and help integrate them into reusable applications
• Provide genomic data analysis to support DF discovery project review and progression, including consulting with academic labs to ensure sound methods and interpretation of data
• Provide bioinformatics consulting for Deerfield portfolio companies that lack internal expertise
• Provide training to Deerfield staff, portfolio companies, and collaborators in genomics applications
• Participate in the development of the Deerfield drug discovery and development data strategy, including genetics, genomics, assays, chemistry, and clinical data
• Contribute to private investment due diligence
• Contribute to the evaluation of clinical development programs
• Expedite recurring analysis requirements by deployment of one-click, well-designed, version-controlled pipelines
• Collect ideas, and requests across the team, and translate them into computational languages to design and develop a database for metadata/results storage.

Skills: Genomic Data Integration, Target Identification, Database Development, Analytics Development, Bioinformatics Consulting, Genomics Training, Drug Discovery Strategy, Clinical Program Evaluation

• Integrate internal and external complex datasets to perform bioinformatics and statistical analysis on biomarker identification, and to provide services and support across a range of R&D projects.
• Collaborate with molecular biologists, translational research scientists, and medicinal chemists, to develop cutting-edge computational methodology, to analyze and interpret various biomarker studies (genetics, gene expression, etc).
• Assist supervisor in managing the established computational tools and pipelines, testing new methods, and optimizing procedures for R&D projects.
• Manage multiple projects simultaneously to deliver high-quality results in a time-sensitive environment.
• Communicate results and findings to key internal stakeholders.
• Guide and/or create user tools for easy access to internal results by scientists.
• Responsible to improve and expand platform analysis capabilities.
• Analyze large data sets and translate findings into actionable experimental designs
• Present scientific material (written and oral)
• Writing and cross-checking code to run standard bioinformatics tools and internal platforms
• Identify and interpret genomic, transcriptomic, and other high-throughput data sets

Skills: Bioinformatics Analysis, Biomarker Identification, Computational Methodology Development, Pipeline Management, Data Interpretation, Platform Expansion, Scientific Communication, High-Throughput Data Analysis

• Leads/co-leads a multi-disciplinary team of biologists, chemists, and pharmacologists to progress drug discovery projects from target validation and discovery implementation to clinical development candidate nomination
• Recruits, oversees, and mentors a team of biologists to validate novel allosteric oncogenes, execute biology strategy, and implement screens to effectively drug allosteric oncogene targets
• Stays abreast of the latest scientific and competitive developments and applying knowledge to project strategy.
• Drives new technology development to support the evaluation of oncogenic mechanisms and effective drug discovery
• Represents project teams and reports project updates to the Research Leadership Team including preparing and presenting hypotheses, ongoing progress reports, technical reports, and future planning (including contributing to budgets and business plans)
• Contributes to building a culture that embraces scientific excellence and integrity with a sense of urgency and collaboration with key stakeholders.
• Develop and implement novel computational approaches to translate human genetic and genomic evidence to drive decisions on target selection, validation, clinical biomarker discovery and patient stratification.
• Find innovative solutions and work with agility to address challenging scientific questions that progress the GSK pipeline.
• Participate in or lead cross-functional project teams with GSK scientists and external collaborators.
• Be responsible for effective communication of analysis findings, with expert interpretation, to relevant stakeholders and project teams.
• Contribute to the developing science of drug target identification and validation, providing scientific expertise within Human Genetics and across the Research organization

Skills: Drug Discovery Leadership, Team Mentorship, Target Validation, Technology Development, Project Management, Scientific Communication, Computational Approaches, Cross-Functional Collaboration

• Research and develop computational methods to transform sequencing data into actionable clinical findings and research insights.
• Improve algorithms and methods implementation to produce very high-performance, production-grade analysis software.
• Design and develop pipelines to address novel analytical challenges
• Assist with the development of computational and software frameworks capable of running multiple Next Generation Sequencing (NGS) pipeline architectures in local and hpc Play a key role in analyzing metagenomics data for high throughput analysis of genomic sequences and contributing analysis to publications
• Play a key role in providing bioinformatics input to partners, including incorporation of new tools and pipelines into current practice
• Interact and collaborate with colleagues and external scientists and other collaborators to ensure the scientific relevance of data analysis and interpretation
• Responsible for supporting large data processing and analysis generated internally, planning and executing computational analysis for multiple project teams.
• Responsible for working with other disciplines such as IT to define infrastructure needs
• Generate and support the generation of IP for core projects
• Validation, optimization and automation of tools, building and maintenance of local databases, generating phylogenetic trees and other data visualization reports, installing software packages and third-party tools, maintenance of computers (Windows, Linux and Linux cluster), and participation in face-to-face and web-based meetings

Skills: Computational Method Development, Algorithm Optimization, Pipeline Design, NGS Data Analysis, Bioinformatics Collaboration, Large Data Processing, Infrastructure Planning, Tool Validation and Automation

• Experience and evidence of scientific leadership 
• Demonstrated track record of delivering cutting-edge research in bioinformatics and computational systems immunology as evidenced by high-impact publications and significant contributions to the field
• Deep experience with some or all of the following single-cell technologies - FACS, CyTOF, single-cell RNA-seq, single-cell epigenomics
• Good understanding of immunology and disease transitions
• Proven track record of setting and meeting goals/milestones/deliverables across multiple projects
• Good oral and written communication skills in presenting analysis of complex data types
• Deep expertise in R and/or Python, Git, Unix shell scripting, and batch processing
• Proven ability to work and think across disciplines
• Strong teamwork skills and ability to coordinate collaborations with the Institute’s Experimental Immunology and Molecular Biology teams and with research partners
• Be collaborative, a team player and demonstrate curiosity
• Ability to engage in crucial conversations – providing and receiving feedback

Qualifications: BS in Bioinformatics with 8 years of Experience

• Broad knowledge of NGS analysis tools and methods, and enough experience to quickly and judiciously evaluate new methods and tools.
• Extensive experience with developing commercial-level pipelines, their underlying statistics and algorithms, and troubleshooting problems.
• Should be comfortable in a Linux shell and with command line tools, and have good software development habits (source control, testing, code reviews).
• Experience with running pipelines in the cloud or on local hardware
• Experience in setting up infrastructure with minimal external assistance.
• The ability to build test programs
• Strong programming skills C++, and/or Python
• Experience working with lab scientists.
• Understanding of cancer biology or immunology.
• Experience with tertiary analysis methods (pathway analysis, biomarker discovery, etc)
• Experience with variant-calling or gene editing pipelines, and with single-cell NGS

Qualifications: BS in Computational Biology with 7 years of Experience

• Relevant work experience in the industry
• Deep understanding of DNA sequencing data and its analysis (mapping, variant calling, etc.)
• Experience with the analysis of NIPT data
• Experience programming in Java and/or Python
• Experience using Linux command-line tools and writing shell scripts
• Solid working knowledge of the key public reference databases for clinical variation data
• Proficiency in one or more of the following fields - metabolic modeling, phylogenetic analyses, deep learning, systems and control theory, graph theory, and systems biology.
• Familiarity with a broad range of programming languages (Julia, C and derivatives, Java).
• Ability to summarize results orally and in written form
• Self-motivated and detail-oriented
• Excellent oral and written communication skills

Qualifications: BS in Systems Biology with 6 years of Experience

• Working experience in oncology performing bioinformatics analysis
• Experience in data science and quantitative data analysis.
• Knowledge in cancer biology and genomics. 
• Work/research experience with public genomic data platforms (GEO, CBioPortal, MSigDB, etc, or equivalent).
• Extensive experience of working with R, especially Bioconductor packages. 
• Experience in building and testing customized R packages.
• Experience in performing complex data analysis on large volumes of data and presenting findings to collaborators
• Experience in drafting and publishing scientific research papers and addressing comments and feedback from collaborators and reviewers.
• Familiar with a Linux environment and shell scripting. 
• Experience working with source control tools (Git) in a collaborative programming environment.
• Strong interpersonal and communication skills (both written and verbal), ability to communicate with people in a wide variety of areas and at various levels from technical specialists to executives

Qualifications: BS in Genetics with 8 years of Experience

• Experience in bioinformatics, biology, mathematics, data mining or engineering.
• Working experience in the medical or biological field.
• Experience with statistics, engineering or data mining.
• Experience with next-generation sequencing data analysis.
• Experience with public databases (e.g., NCBI, UCSC, gnomAD, etc).
• Excellent skills in Linux shell scripting, and Python programming.
• Solid understanding of the multiple comparisons problem and overfitting.
• Strong knowledge of next-generation sequencing data formats.
• Strong skills in mathematics, logic and statistics.
• Project experiences with gene expression analysis and methylation analysis.
• Experience working with Apache Airflow.

Qualifications: BS in Biotechnology with 5 years of Experience

• Prior work experience in computational biology, bioinformatics or related settings 
• Oncology experience with biological background
• Experience handling clinical data 
• Experience in high dimensional data integration and analysis, gene expression analysis, next-generation sequencing analysis and pipeline/tool development, survival analysis, and/or biological network inference.
• Proficiency with classification and machine learning methods with strong R programming skills 
• Statistical analysis experience with working knowledge of regression analysis, multivariate data analysis, and linear/nonlinear mixed effects modeling
• Experience with Bioconductor 
• Working experience in Unix/Linux environment 
• Cloud-based analysis experience 
• Scripting language experience (e.g. bash, Perl or Python)
• Other high-level programming (Java, C++, etc.) and database (e.g. MySQL, PostgreSQL, Oracle) experience 

Qualifications: BS in Molecular Biology with 9 years of Experience

• Experience working with WES, WGS, RNAseq, TCR-sequencing, and/or single-cell sequencing data.
• Working knowledge of cancer genomics and immunology or the ability to learn quickly.
• Strong grasp of methods and tools for statistical inference and machine learning.
• Proven ability to work effectively with a cross-functional team.
• Ability to write clear and effective code in bash, R, Python, and/or C++.
• Strong communication and time management skills.
• Experience with workflow management software includes Snakemake, Cromwell, reflow, WDL, and others.
• Experience with software development in a cloud environment (AWS)
• Ability to create containerized workflows with docker.
• Familiarity with git and/or other version control systems
• Ability to quickly and efficiently adapt to new concepts and collaborate with cross-function teams and business units.

Qualifications: BS in Biophysics with 7 years of Experience

• Experience using code-based translational data analysis and algorithm development to help translate research into clinically actionable insights
• Demonstrated excellence in translational research ( immunology, cancer biology, flow/FACS, imaging, single-cell assays)
• Advanced skills in a high-level programming language, preferably R or Python
• Ability to use R statistical analysis software - good understanding of biological statistics
• Experience with data visualization in Python or R - (R- ggplot, Plotly, Rshiny, Python- Bokeh, Seaborn)
• Knowledge of Linux or Unix command line, optionally with Java or C/C++, TABLEAU
• An understanding of machine learning, data modeling, or statistical techniques, such as mixed-model regression, principal component analysis, classifier construction and validation, biomarker discovery, and optimization methods
• Experience with architecture and tools for managing “omics” data OR imaging data
• Ability to work independently and as part of a team while being collaborative in resolving problems
• Excellent communication, analytical, and organizational skills, both written and verbal
• Ability to prioritize multiple tasks at one time

Qualifications: BS in Applied Mathematics with 10 years of Experience

• Hands-on experience in the fields of bioinformatics and genomics including working with various public and proprietary data repositories (e.g., TCGA, GTEx, dbGaP, Ensembl, UCSC genome browser, Array Studio), bioinformatics tools (e.g., BLAST, GATK, Cell Ranger, samtools, VEP), and statistical environments (e.g., R, S+, Matlab)
• Demonstrated ability to understand data, apply techniques to interpret data, and summarize conclusions (orally and on paper)
• Demonstrated experience handling high fidelity/highly rigorous data supporting regulatory submissions
• Expert with graphical modeling approaches, tools and model repositories
• Strong use of statistical, algorithmic, mining and visualization of data techniques
• Quickly and easily create custom pipelines for data analysis
• Passion and creativity to solve scientific problems through the lens of data analysis
• Excellent numeracy and English language skills (both written and verbal)
• Excellent communication skills (both written and verbal)
• Attention to detail, good time management skills, ability to engage with urgency
• Strong team player, able to partner with others responsible for tools and process

Qualifications: BS in Computer Science with 9 years of Experience

• Experience processing, analyzing and integrating multiple NGS-based data sets.
• Microbiome research working experience
• Synthetic Biology working experience
• Understanding of Molecular Biology/Genetics assays
• Linux scripting abilities and working knowledge of at least one program language (e.g., R, Pearl, Python, C++).
• Strong background in statistics/machine learning applied to systems-level data types.
• Strong background in Biology with highly motivated.
• Strong independence in carrying out research tasks.
• Collaborative with excellent written and verbal communication skills, and the ability to interact with people from diverse areas and disciplines.
• A good working knowledge of the integration of multiple --omics platform data
• Experience integrating lower-level hardware interfaces (TCP/IP, serial ports, etc).

Qualifications: BS in Data Science with 7 years of Experience