Job Summary: 

• Provide high-level insight and guidance in biomarker strategies by contributing novel approaches and incorporating new technological capabilities 
• Track predictive biomarker strategy progress through assay development, data analysis to data presentation
• Matching company resources and technologies to developmental plans 
• Ensure alignment for predictive biomarker and patient selection strategies to ensure successful translation from preclinical project to clinical development 
• Help Guide biomarker discovery research projects to generate data that justify and/or inform the collection and analysis of clinical specimens 
• Develop and assist in the documentation of novel IP related to biomarker discoveries
• 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.
• Identify biases within sequencing data to improve experimental design and process development. 

Skills on Resume: 

• Biomarker Strategies (Hard Skills)
• Assay Development (Hard Skills)
• Data Analysis (Hard Skills)
• IP Documentation (Soft Skills)
• Statistical Analysis (Hard Skills)
• Machine Learning Models (Hard Skills)
• Technology Innovation (Hard Skills)
• Experimental Design (Soft Skills)

Job Summary: 

• Collaborate with bench scientists to design and execute computational analysis of large-scale molecular data from preclinical research. 
• Collaborate with translational oncologists on analysis of early-stage clinical trials molecular data. 
• Conduct in silico analysis to help address questions such as predictive biomarkers, tumor indication, drug combination and resistance mechanisms. 
• Process, analyze and interpret high dimensional data from diverse OMICS platforms. 
• Contribute to the development of data packages supporting decision-making. 
• Actively participate in project teams with multidisciplinary backgrounds to formulate data-driven, actionable hypotheses. 
• Devise and leverage state-of-the-art computational approaches for oncology target identification and precision medicine. 
• Contribute effectively to a shared codebase that can be leveraged broadly for multiple applications.
• Work closely with a multi-disciplinary team of scientists and engineers to develop powerful computational tools for DNA sequencing applications. 
• Set up, maintain, and utilize automated data processing pipelines to support internal R&D and external collaborations in the area of NGS-sequence analysis. 

Skills on Resume: 

• Computational Analysis (Hard Skills)
• Translational Oncology Collaboration (Soft Skills)
• In Silico Analysis (Hard Skills)
• High Dimensional Data Processing (Hard Skills)
• Data Package Development (Hard Skills)
• Multidisciplinary Team Collaboration (Soft Skills)
• Computational Oncology Tools (Hard Skills)
• NGS-Sequence Analysis (Hard Skills)

Job Summary: 

• Be responsible to lead the computational biology effort and build it from the ground up. 
• Be responsible to improve and expand platform analysis capabilities. 
• Analyze large data sets and translate findings into actionable experimental designs 
• Have a deep understanding of RNA Biology (structure-function, interactions)
• Be responsible for supporting large data processing and analysis generated internally
• Planning and executing computational analysis for multiple project teams. 
• Have experience in developing analysis pipelines. 
• Be responsible for working with other disciplines such as IT to define infrastructure needs 
• Generate and support the generation of IP for core projects 
• Interpret and glean valuable insights from data. 
• Present approaches and findings to experimentalists and management.

Skills on Resume: 

• Computational Biology Leadership (Soft Skills)
• Platform Analysis Improvement (Hard Skills)
• Large Data Set Analysis (Hard Skills)
• RNA Biology Knowledge (Hard Skills)
• Data Processing Support (Hard Skills)
• Computational Analysis Planning (Soft Skills)
• Analysis Pipeline Development (Hard Skills)
• Cross-Disciplinary Collaboration (Soft Skills)

Job Summary: 

• Develop and execute quality assessment routines for translational study datasets contributed by external collaborators. 
• Establish procedures for the execution of quality routines in production.
• Conduct feasibility assessments, supporting studies in precision medicine and immunotherapy. 
• Develop proposals for new studies using consortia/in-house and publicly available datasets.
• Design and conduct analyses and meta-analyses across multiple translational datasets.
• Summarize research findings in reports, manuscripts, and presentations to collaborators and funders.
• Develop new methods, pipelines, and tools for analysis of data from funded projects, in collaboration with external partners. 
• Generate preliminary data to support grant applications.
• Collaborate with in-house data curation experts to select and apply data standards to consortia datasets.
• Pilot methods to use cloud computing resources to analyze datasets held in Sage’s Synapse data-sharing platform.
• Work with Sage’s software engineering team to define use cases and requirements for new features in Synapse.

Skills on Resume: 

• Quality Assessment Routines (Hard Skills)
• Feasibility Assessments (Hard Skills)
• Study Proposal Development (Soft Skills)
• Translational Data Analysis (Hard Skills)
• Research Summarization (Soft Skills)
• Pipeline and Tool Development (Hard Skills)
• Data Standards Application (Hard Skills)
• Cloud Computing Methods (Hard Skills)

Job Summary: 

• Integrate multi-dimensional data types capturing the dynamic and spatial complexity 
• Transcriptional regulation across relevant conditions, stimulations, and treatment paradigms
• Collaborate closely with experimental and data science colleagues 
• Guide mechanism-driven drug development, including in the context of biotech collaborations and publications
• Providing conceptual input into analysis plans (approaches and design)
• Engage in cross-functional discussions to refine plans and identify key priorities
• Completing computational data analysis as specified
• Analyze plans, visualize and provide interpretation and context to the results of the analysis
• Identify, evaluate, and apply new methodologies and emerging technologies, and develop software tools
• Demonstrating an exceptional work ethic by taking the initiative and working with a sense of urgency to discover breakthrough medicines 
• Improve patients’ lives, collaborate and share ideas with the rest of the team, and challenge the status quo

Skills on Resume: 

• Multi-Dimensional Data Integration (Hard Skills)
• Transcriptional Regulation Analysis (Hard Skills)
• Collaborative Work (Soft Skills)
• Mechanism-Driven Drug Development (Hard Skills)
• Conceptual Input in Analysis Plans (Soft Skills)
• Cross-Functional Collaboration (Soft Skills)
• Computational Data Analysis (Hard Skills)
• Methodology Evaluation and Software Tool Development (Hard Skills)

Job Summary: 

• Analyze and integrate various clinical and omics data from public repositories (DepMap, TGCA, ENCODE, SRA, etc.)
• Develop or deploy new methods to utilize new technologies
• Employ Client/AI methods to draw preclinical and molecular insights from omics data
• Prioritize results based on biological evidence from various resources
• Present research findings and contribute to publications/manuscript preparation
• Document code, analyses and streamline workflows
• Analyze data from Genome editing and siRNA therapeutics - from off-target predictions and experimental data analyses.
• Work on NGS approaches for the characterization of packaged AAV genomes and support product and analytical development.
• Present results and progress updates at lab meetings and lead presentations to experimental and scientific collaborators
• Design gene therapy and genome editing approaches based on comparative genomics analysis (CDS Optimization, promoter and shRNA design).
• Attend seminars, lectures, and training courses to learn new computational biology skills to remain up to date with the cancer genomics field and learn new programming languages or techniques

Skills on Resume: 

• Clinical and Omics Data Integration (Hard Skills)
• New Method Development (Hard Skills)
• Client/AI Methods Application (Hard Skills)
• Result Prioritization (Soft Skills)
• Research Presentation (Soft Skills)
• Code Documentation (Hard Skills)
• NGS and Genome Editing Analysis (Hard Skills)
• Gene Therapy Design (Hard Skills)

Job Summary: 

• Design, develop and operate computational pipelines to analyze next-generation sequencing data.
• Analyze data sets to discover and annotate cancer-causing genetic mutations in tumor specimens.
• Evaluate the performance of novel technology platforms and assays
• Collaborate with research groups to analyze biomedical data and address scientific problems with bioinformatics techniques and tools
• Train researchers in the use of computational and bioinformatics tools
• Develop, refine, and improve bioinformatics tools to interpret sizeable genomic data sets.
• Evaluate and test third-party software packages.
• Track specimen information, experimental and analysis parameters, performance metrics, and genomic results in databases
• Manage and archive large data sets from next-generation sequencing experiments
• Participate in the establishment and maintenance of a Laboratory Information Management System (LIMS)
• Install and maintain software and data, and maintain detailed records of all analysis

Skills on Resume: 

• Computational Pipeline Development (Hard Skills)
• Genetic Mutation Analysis (Hard Skills)
• Technology Platform Evaluation (Hard Skills)
• Bioinformatics Collaboration (Soft Skills)
• Researcher Training (Soft Skills)
• Bioinformatics Tool Development (Hard Skills)
• Software Evaluation (Hard Skills)
• Data Management (Hard Skills)

Job Summary: 

• Work as a core member of the bioinformatics group, contributing to the continued success and development of the SITESEEKER® platform and drug discovery campaigns
• Design and execute computational analysis and R&D tasks to support programs
• Apply expertise in AI and mathematical tools and interpret both experimental and modeled data accurately and precisely
• Devise and develop new tools, workflows and strategies to understand data in new ways
• Interact and collaborate with biologists and other computational scientists on the team
• Keep up to date with the latest ML/AI research and developments through publications and relevant conference attendance
• Document and communicate findings clearly to colleagues and senior leadership
• Generate insights from high-throughput data to answer questions in neuroscience - WGS, Single-cell, bulkRNA-seq, ChipSeq, and CRISPR screens.
• Engage external resources to apply cutting-edge methodologies and ensure recognition in the scientific community including publications
• Interact and collaborate with data scientists and team members daily
• Serve as bioinformatics specialist to support research and development focusing on Alkahest's genomics efforts

Skills on Resume: 

• Bioinformatics Collaboration (Soft Skills)
• Computational Analysis (Hard Skills)
• AI and Mathematical Tools Application (Hard Skills)
• Tool and Workflow Development (Hard Skills)
• ML/AI Research Updates (Soft Skills)
• High-Throughput Data Insights (Hard Skills)
• Scientific Communication (Soft Skills)
• Genomics Support (Hard Skills)

Job Summary: 

• Analyze and visualize GWAS and MR data using published or custom scripts.
• Work closely with biologists and bioengineers to develop tools that advance the therapeutic pipeline
• Develop algorithms and statistical inference to gain insight into high-throughput screening systems for molecular engineering
• Generate data visualizations for high-throughput and high-dimensional data
• Develop and maintain a version-controlled code base, and ensure team members are trained in the use
• Effectively communicate analysis approaches with close collaborators and across the company
• Foster a driven, fast-paced, dynamic, and fun environment in which to do rigorous science
• Integrate multi-omics data across all layers of biology from genetics to disease 
• Analyze large-scale biomarker datasets (phenomics, proteomics, metabolomics, and lipidomics) outcomes
• Implement epidemiological models to define the physiological process involved in aging to identify causal pathways for intervention studies
• Assist others in interpreting findings and in testing hypotheses to help us develop targeted therapeutics

Skills on Resume: 

• GWAS and MR Data Analysis (Hard Skills)
• Tool Development for Therapeutic Pipeline (Hard Skills)
• Algorithm and Statistical Inference Development (Hard Skills)
• Data Visualization (Hard Skills)
• Version-Controlled Code Base Management (Hard Skills)
• Effective Communication (Soft Skills)
• Multi-Omics Data Integration (Hard Skills)
• Epidemiological Modeling (Hard Skills)

Job Summary: 

• Perform professional work in support of scientific research using technical knowledge of software, software development, networking, and/or hardware in a complex computing environment.
• Works collaboratively with the Principal Investigator to determine the most suitable computational methods and tools to analyze large-scale biological data sets.
• Prepare reports for presentation or publication.
• Manage research laboratory computer hardware and software programming and maintenance.
• Ensure existing systems meet the continuing needs of the lab and/or recommend and test new systems
• Perform complex data analysis related to specialized research methodologies and results as assigned by the PI.
• Develop and/or modify software to support new and ongoing research projects.
• Resolve hardware, software, and network issues in support of the lab.
• Responsible for assisting PI in meeting the system needs by developing and maintaining complex databases to support multiple new and ongoing research projects and/or labs.
• Train laboratory staff in the use of pertinent research systems.
• Specialize in bioinformatics, software development, network administration, or hardware/software maintenance.

Skills on Resume: 

• Computational Method Selection (Soft Skills)
• Report Preparation (Soft Skills)
• Laboratory System Management (Hard Skills)
• Complex Data Analysis (Hard Skills)
• Software Development (Hard Skills)
• Hardware/Software/Network Troubleshooting (Hard Skills)
• Database Management (Hard Skills)
• Staff Training (Soft Skills)

Job Summary: 

• Select, test, implement and optimize image processing, image analysis, and machine learning methods to extract relevant signals from imaging data.
• Build analytical models or simulations to understand and communicate key trade-offs of system design from image acquisition to final analysis.
• Rapidly prototype methods for internal experiments and early R&D.
• Create high-quality, robust implementations of production algorithms.
• Identify and develop optimal algorithms and workflows to analyze GWAS and MR datasets, separately and integratively.
• Identify and integrate relevant external datasets to aid in the analysis and interpretation of internal data
• Ensure completeness, critical evaluation, correctness and integrity of analyses and datasets
• Manage the storage and compression of over 5Pb of internally generated sequencing data as well as the download and storage of external data.
• Test and validate new data analysis software for analyses such as alignment, duplicate marking and merging.
• Participate in code walk-throughs and reviews of solutions.
• Work closely with the GSC Systems team and Quality Assurance team to establish and carry out best practices for data security, and ensure compliance with ISO 27001 certification, CAP/DAP clinical accreditation requirements and other data use agreements

Skills on Resume: 

• Image Processing and Analysis (Hard Skills)
• Analytical Model Development (Hard Skills)
• Rapid Prototyping (Hard Skills)
• Production Algorithm Implementation (Hard Skills)
• GWAS and MR Dataset Analysis (Hard Skills)
• External Dataset Integration (Hard Skills)
• Data Management and Compression (Hard Skills)
• Data Security Compliance (Soft Skills)

Job Summary: 

• Assist in the development and maintain the core sequence analysis pipelines at GSC
• Formatting and manipulation of alignment files for use by downstream pipelines (e.g. merging, re-heading)
• Assist in the development and maintain GSC laboratory, quality and analysis databases
• Routine database integrity checks and database maintenance
• Development of views and interfaces for data entry
• Development of reports for internal users and collaborators
• Investigation of new frameworks and designing new schemas and tables
• Participate in the development and maintains ETL pipelines between GSC production databases.
• Implement and document reliable and efficient web applications with well-designed user interfaces.
• Communicate with stakeholders in the lab, on analysis teams, and with external collaborators to understand and document requirements for development and to respond to questions about collaborator data and data quality.
• Work with upstream and lab teams generating data to be housed in the database, and with downstream users of the databases to meet requirements, and respond to internal requests for query and API support.

Skills on Resume: 

• Sequence Analysis Pipeline Development (Hard Skills)
• Alignment File Manipulation (Hard Skills)
• Database Development and Maintenance (Hard Skills)
• Database Integrity Checks (Hard Skills)
• Data Entry Interface Development (Hard Skills)
• Report Development (Hard Skills)
• ETL Pipeline Development (Hard Skills)
• Stakeholder Communication (Soft Skills)

Job Summary: 

• Maintain and develop NGS sequencing pipelines in the Google Cloud Platform.
• Run pipelines to process incoming sequencing data generated from clinical trials.
• Collaborate with laboratory researchers to perform downstream analysis and generate biological insights from clinical trial data.
• Communicate results to immediate collaborators, as well as bioinformatics and clinical communities.
• Working with scientists at Sage and external collaborators in academia and industry to develop bioinformatic analyses and visualizations of genomic data.
• Analyzing high-dimensional genetic, bulk transcriptomics, and/or single-cell sequencing data including statistical modeling and visualization.
• Performing and documenting analyses and workflows using reproducible programming techniques.
• Collaborate with other bioinformaticians on reproducible workflows, shared methods, and community code projects (e.g. GitHub).
• Working with software engineers and cloud architects to automate workflows and build robust infrastructure.
• Writing technical documentation for a scientific audience, co-authoring scientific papers for peer-reviewed journals, and presenting work at scientific conferences.
• Perform cross-trial analysis integrating multiple data types in the CIDC data portal to identify new biomarkers for immunotherapy using statistical modeling or machine learning approaches.

Skills on Resume: 

• NGS Pipeline Development (Hard Skills)
• Clinical Trial Data Processing (Hard Skills)
• Downstream Data Analysis (Hard Skills)
• Results Communication (Soft Skills)
• High-Dimensional Data Analysis (Hard Skills)
• Reproducible Programming (Hard Skills)
• Workflow Automation (Hard Skills)
• Scientific Documentation (Soft Skills)

Job Summary: 

• Be part of and lead a team of data scientists and data engineers
• Apply predictive modeling to leverage single-cell approaches
• Develop solutions to core scientific problems
• Articulate and solve large problems by breaking them down into actionable points
• Work with clinical and pre-clinical teams
• Sharing and adhering to coding standards
• Compose personalized genomics reports resulting from extensive research on specific genetic conditions or polygenic diseases
• Analyze and synthesize multiple genomic data sets to improve variant calling, CNV and structural variation analyses, mitochondrial DNA variation, and family-based analysis (transmission, de novo variants)
• Conduct in-depth analyses of genomic datasets to discover potential disease-associated traits
• Manage outsourced genomics bioinformatics work to coordinate and accelerate ICR research programs
• Collaborate with other ICR scientists in translational genomics projects

Skills on Resume: 

• Team Leadership (Soft Skills)
• Predictive Modeling (Hard Skills)
• Scientific Problem Solving (Hard Skills)
• Problem Breakdown (Soft Skills)
• Clinical Collaboration (Soft Skills)
• Coding Standards Adherence (Soft Skills)
• Genomics Report Composition (Hard Skills)
• Genomic Data Analysis (Hard Skills)

Job Summary: 

• Provide scientific and technical leadership of the data science team, including defining the vision and strategy for data science and bioinformatics at LabGenius in collaboration with the leadership team
• Communicate and drive consensus on this strategy and plan with other senior scientists across the company
• Use expertise in immuno-informatics and/or structural biology to drive the team to develop novel methods for predicting protein function and developability, and deploy these to accelerate biotherapeutic discovery campaigns
• Identify and pursue opportunities to improve the platform and drive innovation keeping abreast of relevant bioinformatic developments, standards, tools and technologies
• Provide mentorship to the wider data science team on computational biology, machine learning, statistics, communication and the range of skills needed to be effective in their role
• Be an external-facing voice for data science at LabGenius, including speaking at conferences and collaborating on business development and fundraising
• Design and execute computational analyses to understand molecular mechanisms underlying complex traits in crop species.
• Explore complex genomic and metagenomic data from microbial collections and diverse communities, respectively.
• Integrate and model multi-omics data sets to gain an understanding of plant and microbial biological systems.
• Analyze and present data, both in written reports and oral presentations within the group.
• Take responsibility for pangenome and comparative genomic analysis.

Skills on Resume: 

• Data Science Leadership (Soft Skills)
• Strategy Communication (Soft Skills)
• Immuno-Informatics Expertise (Hard Skills)
• Platform Innovation (Hard Skills)
• Team Mentorship (Soft Skills)
• External Representation (Soft Skills)
• Multi-Omics Data Integration (Hard Skills)
• Pangenome Analysis (Hard Skills)

Job Summary: 

• Design, create and develop novel scientific solutions and concept evaluations based on complex network principles
• Provide scientific strategy and solution to ongoing customer projects
• Be responsible for managing the interfaces with internal and external stakeholders
• Work with Sales Personnel, Customer Success, Product Team, Technical Teams and key business partners to ideate solutions
• Advise and ideate on novel, cutting-edge technologies
• Assess existing software tools and utilize them to solve industry problems
• Understand industry challenges as well as industry drivers, translating them into actionable solutions
• Communicate knowledge to engineering and product development teams to guide product improvements and releases
• Work with cross-functional global teams
• Organize and maintain cloud-based infrastructure for storage and maintenance of NGS data
• Identify and manage external vendors, CROs, and consultants

Skills on Resume: 

• Scientific Solution Design (Hard Skills)
• Scientific Strategy Development (Soft Skills)
• Stakeholder Management (Soft Skills)
• Cross-Functional Collaboration (Soft Skills)
• Technology Ideation (Soft Skills)
• Software Tool Assessment (Hard Skills)
• Industry Problem Solving (Hard Skills)
• Cloud Infrastructure Management (Hard Skills)

Job Summary: 

• Plan, develop and carry out original research.
• Develop and refine computational modeling methods.
• Ensure the validity and reliability of data at all times.
• Research, curation, and analysis of cancer data, including the company’s proteomic database and another omic database.
• Identify high-quality, complementary and relevant data sets to merge with existing data.
• Carry out computational modeling using tools such as BioModelAnalyzer.
• Independently drive projects, plan workflows, and troubleshoot technical and other problems.
• Work in collaboration with other teams and scientists within the company and externally with academic institutions.
• Participate in regular team meetings.
• Interpret results and build effective tools to present findings to project teams in a clear and concise manner
• Act as an internal thought leader on data analysis for target discovery and translational efforts

Skills on Resume: 

• Original Research Planning (Soft Skills)
• Computational Modeling Development (Hard Skills)
• Data Validity Assurance (Hard Skills)
• Cancer Data Analysis (Hard Skills)
• Data Set Integration (Hard Skills)
• Project Management (Soft Skills)
• Collaborative Work (Soft Skills)
• Result Interpretation and Presentation (Soft Skills)

Job Summary: 

• Work with Discovery and Translational scientists in the analysis of preclinical and clinical omics datasets to make novel discoveries at all phases of the drug discovery process
• Develop new methods and algorithms to identify and characterize alterations in tumor DNA and RNA derived from pre-clinical and clinical cancer specimens
• Mine publicly available and proprietary oncology-focused omics databases to make novel insights and generate new hypotheses
• Collaborate with wet lab scientists to design experiments, design molecules, and analyze data
• Perform quick and thorough analyses of DNA sequencing data to understand outliers, make descriptive figures, and address key statistical questions
• Build and evaluate probabilistic models of experimental processes
• Build and modify bioinformatic pipelines for NGS data
• Present results to a wide variety of stakeholders, from wet lab scientists to executive team members
• Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internally and externally in the Laboratory.
• Publish research results in peer-reviewed scientific or technical journals.
• Organize, analyze, and present data from research at seminars, technical meetings, and conferences.

Skills on Resume: 

• Preclinical and Clinical Data Analysis (Hard Skills)
• Method and Algorithm Development (Hard Skills)
• Omics Database Mining (Hard Skills)
• Experimental Design Collaboration (Soft Skills)
• DNA Sequencing Data Analysis (Hard Skills)
• Probabilistic Model Building (Hard Skills)
• NGS Pipeline Development (Hard Skills)
• Research Presentation (Soft Skills)

Job Summary: 

• Implement a computational pipeline to analyze genotype/phenotype/process data from iNK/iT products to identify markers/correlates of functional activity
• Work with the Translational team on biomarker discovery plans and pipelines for upcoming clinical trials
• Work with the Clinical team on clinical trial design
• Collaborate with other researchers in the design of experiments and the analysis of data, discuss statistically valid data collection and sampling methods
• Integrate publicly accessible, commercial, and/or proprietary databases of biological data
• Maintain detailed documentation of all analyses to ensure reproducibility
• Be up to date with current trends in the field of bioinformatics/biostatistics and evaluate state-of-the-art tools and services
• Apply statistical techniques and develop predictive models to understand a range of human phenotypes and disease states.
• Research, design, and implement models that integrate published biomedical information with novel data collection to identify significant trends and predict disease outcomes.
• Perform quality analysis, quality control, and other independent tests of third-party algorithms, analysis methods, and data collection procedures.
• Design computational analyses of diverse phenotypic, molecular, genomic, and metabolic datasets, including those generated by biosensors, bioimaging, whole genome DNA sequencing, or mass spectrometry.

Skills on Resume: 

• Computational Pipeline Implementation (Hard Skills)
• Biomarker Discovery (Hard Skills)
• Clinical Trial Design Collaboration (Soft Skills)
• Experimental Design and Data Analysis (Soft Skills)
• Database Integration (Hard Skills)
• Reproducible Documentation (Hard Skills)
• Statistical Modeling (Hard Skills)
• Quality Control and Validation (Hard Skills)

Job Summary: 

• Perform local splice variant analysis from short-read sequencing data to characterize the effect of small molecules on splicing
• Perform splice-isoform analysis from long-read sequencing data.
• Develop analysis pipelines for novel experimental methods to characterize splice variants.
• Identify novel therapeutic targets that can be perturbed by modulating splicing of the RNA.
• Support programs with internal and external ‘omics data, including single-cell RNA-seq
• Responsible for undertaking and managing software development using structured software engineering best practices. 
• Collaboratively build, publish and re-use high-performance open-source code.
• Develop novel diagnostic, prognostic, and therapy-predictive proof-of-concept solutions across multiple areas of medicine, work strategically with clinical and commercial teams
• Work closely with the Machine Learning Department and other teams to transfer and integrate early discovery results into late-stage development
• Keep abreast of trends and advancements in the research literature concerning biomarker discovery
• Communicate results in weekly team meetings with Computational Biology, Machine Learning, and other teams

Skills on Resume: 

• Splice Variant Analysis (Hard Skills)
• Long-Read Sequencing Analysis (Hard Skills)
• Pipeline Development (Hard Skills)
• Therapeutic Target Identification (Hard Skills)
• Omics Data Support (Hard Skills)
• Software Development Management (Hard Skills)
• Open-Source Code Collaboration (Soft Skills)
• Biomarker Discovery Communication (Soft Skills)

Job Summary: 

• Work with team members to build and maintain a common code repository, bioinformatic best practices and team engagement. 
• Work with investigators to triage requests, establish requirements, communicate ongoing work, interpret results and build community. 
• Work with other cores to collaborate on support of investigator projects and to build and maintain shared workflows and seamless services.
• Wrangle, clean, structure and store investigator data. 
• Provide documentation and user support allowing computational researchers across campus to access and re-use analysis pipelines.
• Establish and employ best practices for omic, imaging and integrative data representation and analysis. 
• Work with biostatisticians to model data, identify significant effects related to experimental and technical factors in data generation and processing, reduce dimensionality, and develop and validate biological conclusions that drive the next generation of research and advance human health.
• Develop and provide documentation and user support allowing biomedical researchers around the world to access and re-use analysis tools/workflows.
• Participate in appropriate activities that enhance general knowledge of or ability to do assigned work.
• Assist in building, populating and/or maintaining a searchable, browsable system storing raw omic and imaging data, sample metadata, data generation and data processing provenance, and custom analysis results.
• Work with platform development teams to implement scalable high-performance workflows to support the research community with analytical advances and to disseminate best practices to the computational community. 

Skills on Resume: 

• Code Repository Management (Hard Skills)
• Investigator Collaboration (Soft Skills)
• Workflow Collaboration (Soft Skills)
• Data Wrangling (Hard Skills)
• Documentation and User Support (Soft Skills)
• Omic and Imaging Data Analysis (Hard Skills)
• Biostatistical Modeling (Hard Skills)
• Scalable Workflow Implementation (Hard Skills)

Job Summary: 

• Partner cross-functionally with key stakeholders within product and technology teams while effectively driving multiple program delivery in the diagnostic and therapeutic space
• Understand and manage risks and dependencies in a startup environment
• Provide clarity on objectives, and deliverables, and define scopes accurately for each program
• Take charge of planning, communications, change management, and implementation within projects and programs
• Navigate diverse stakeholder groups, form and sustain successful partnerships with made of experts with overlapping and non-overlapping expertise
• When the need arises, build and manage the program management team
• Identify risks early on, and work diligently with the appropriate subject matter experts to solve or mitigate issues and ensure the timely continuation of program deliveries
• Present to and exchange with the senior management team to align tactical execution and ability to deliver high-level strategic plans
• Build relationships and collaborate with key stakeholders to ensure great delivery
• Champion the value of program management at the company
• Write technical reports and manuscripts

Skills on Resume: 

• Cross-Functional Collaboration (Soft Skills)
• Risk Management (Soft Skills)
• Program Scoping (Hard Skills)
• Change Management (Soft Skills)
• Stakeholder Partnership (Soft Skills)
• Program Management Team Building (Soft Skills)
• Strategic Alignment (Soft Skills)
• Technical Report Writing (Hard Skills)

Job Summary: 

• Collaborate with the immunology team to design and analyze high-dimensional biological datasets (e.g. bulk RNA-seq, ATAC-seq, scRNAseq, scATACseq, CITE-seq)
• Develop novel computational methods or use existing methods to analyze datasets from various sequencing technologies and understand the key role of the immune system
• Develop novel computational methods, and use existing methods, to analyze data from mammalian cells with varying genetic backgrounds to assist in the design and assessment of gene-editing experiments
• Integrate multi-modal datasets to derive insights for key biological questions
• Formulate testable biological hypotheses and collaborate in the design of rigorous preclinical experiments
• Work closely with various multi-disciplinary teams on the design of experiments and analysis of data
• Communicate results both internally and to a broad scientific audience
• Bring emerging methods and technologies in computational biology and sequencing platforms
• Initiate and guide the generation/analysis of top-quality genetic and genomic data in close collaboration with various teams
• Contribute to the integration of multi-modality systems biology data
• Develop computational tools and workflows that support these activities

Skills on Resume: 

• High-Dimensional Data Analysis (Hard Skills)
• Computational Method Development (Hard Skills)
• Gene-Editing Experiment Design (Hard Skills)
• Multi-Modal Data Integration (Hard Skills)
• Hypothesis Formulation (Soft Skills)
• Cross-Disciplinary Collaboration (Soft Skills)
• Scientific Communication (Soft Skills)
• Computational Tool Development (Hard Skills)

Job Summary: 

• Perform bioinformatics analysis on data generated from gene editing assays (e.g., gRNA design, GUIDE-Seq, and Amp-Seq), and work closely with research teams to deliver outcomes and insights
• Develop bioinformatics pipelines by integrating and extending existing bioinformatics and next-generation sequencing (NGS) tools
• Streamline the data analysis with workflow management tools (e.g., Snakemake, Nextflow), and scale up the analysis in the cloud environment (e.g., AWS)
• Partner with research and development teams on project management, provide data-driven recommendations to decision-makers
• Help the company understand FDA policy and guidance in the bioinformatics area relevant to the regulation of cell and gene therapy products
• Work with regulatory authorities to standardize the bioinformatics workflow inhouse and prepare scientific study reports for regulatory submission
• Support the development of a biological network model relevant to toxicological assessment studies
• Process gene expression datasets, perform analyses, and support the biological interpretation of the results
• Work with software engineers and product designers to bring those tools into the production pipeline.
• Analyze the world’s largest collection of clinical and molecular data from cancer patients to identify new scientific insights.
• Share those insights with the greater scientific and medical community through publication.

Skills on Resume: 

• Bioinformatics Analysis (Hard Skills)
• Pipeline Development (Hard Skills)
• Workflow Management (Hard Skills)
• Project Management Collaboration (Soft Skills)
• FDA Policy Understanding (Soft Skills)
• Regulatory Workflow Standardization (Hard Skills)
• Gene Expression Data Analysis (Hard Skills)
• Scientific Insight Sharing (Soft Skills)

Job Summary: 

• Collaborate with internal stakeholders to design, conduct and document analyses in support of scientific objectives.
• Analyze large immune sequencing datasets using statistical analysis and machine learning techniques in a Python-centric cloud environment.
• Evaluate and synthesize cellular immunology data, including for example matching of TCRs to antigens at scale.
• Interpret and provide recommendations for new analyses and models that drive innovation.
• Adapt quickly to changing priorities and generate innovative solutions in a fast-paced environment.
• Work with biologists to define innovative features/signals in large-scale immune sequencing data that can improve assays or machine learning performance.
• Develop new algorithms and rapidly prototype new approaches to take the best advantage of the type and scale of data being generated.
• Support Adaptive's Drug Discovery partnerships through thoughtful analysis and presentation of results across programs and to internal and external senior leadership.
• Ensure clear synthesis, interpretation, and sharing of results to drive innovation, technology and platform improvements, and therapeutic product development.
• Design and develop new computational tools and assays for clinical genomics platforms to improve patient care.
• Work with the experimental team to leverage metagenomics to supplement experimental lab work

Skills on Resume: 

• Stakeholder Collaboration (Soft Skills)
• Immune Sequencing Data Analysis (Hard Skills)
• Cellular Immunology Data Evaluation (Hard Skills)
• Analytical Recommendations (Soft Skills)
• Adaptability (Soft Skills)
• Feature Definition in Sequencing Data (Hard Skills)
• Algorithm Development (Hard Skills)
• Results Presentation (Soft Skills)

Job Summary: 

• Develop and revise high-performance next-generation sequencing (NGS) data analysis pipeline systems, to analyze data in a reliable and timely fashion.
• Develop complex data integration methods/algorithms across various NGS sequencing techniques (ChIP-seq, RNA-seq, Hi-C, etc).
• Lead or participate in brainstorming sessions to seek reliable solutions for complex data analysis related to specialized research methodologies.
• Oversee the development and maintenance of complex databases to support new and ongoing research projects.
• Investigate/solve complex problems involving interesting and sometimes puzzling data.
• Manage computer hardware and software programming and maintenance for one or more research laboratories in the core. 
• Ensure existing systems meet the continuing needs of the labs and/or recommend and test new systems
• Prepare research reports for presentation sometimes to a broad range of non-computational staff and assist with the preparation of manuscripts for publication
• Develop tools to classify and characterize proteins of unknown function
• Computationally investigate protein diversity, and analyze large-scale metagenomic databases
• Genome assembly and annotation from environmental sequencing samples

Skills on Resume: 

• NGS Pipeline Development (Hard Skills)
• Data Integration Algorithm Development (Hard Skills)
• Brainstorming and Problem Solving (Soft Skills)
• Database Development and Maintenance (Hard Skills)
• Complex Data Investigation (Hard Skills)
• Laboratory System Management (Hard Skills)
• Research Report Preparation (Soft Skills)
• Protein Classification Tool Development (Hard Skills)