Job Summary: 

• Collaborate with experimentalists and computational scientists across the company to develop robust data science approaches to target identification and validation
• Integrate multiple levels of biological information to inform genome-protein-disease networks in the context of drug discovery
• Develop supporting evidence for the functional relevance of targets in human diseases and recommend follow-up experiments
• Help prioritize and triage potential drug targets using computational expertise and domain knowledge
• Identify novel data sources, computational methods, and external collaborations that will grow capabilities in computational target validation
• Assist in the preparation of scientific presentations, manuscripts and reports
• Interpret and communicate analytical information in a clear, concise manner
• Desire to work and problem-solve in a highly collaborative team environment, where colleagues frequently depend on one another
• Be open and transparent, holding themselves to high standards of scientific rigor and honesty
• Creates and presents tutorials, hands-on workshops, and documentation to train the research community.

Skills on Resume: 

• Collaboration With Scientists (Soft Skills)
• Biological Data Integration (Hard Skills)
• Evidence Development For Targets (Hard Skills)
• Target Prioritization (Hard Skills)
• Novel Data And Methods Identification (Hard Skills)
• Scientific Presentation Preparation (Soft Skills)
• Clear Analytical Communication (Soft Skills)
• Team Problem-Solving (Soft Skills)

Job Summary: 

• Works closely with faculty to identify, develop, and implement useful computational methods and resources that support or advance their research. 
• Independently and proactively proposes and executes practical solutions to research challenges.
• Implements machine learning algorithms and summarizes findings.
• Develops, maintains, and supports data analysis and machine learning pipelines that include data collection, data management, data transformation, data analysis and documentation.
• Serves as the RCC Visualization laboratory point person. 
• Develops and maintains data visualization software and tools. 
• Assists faculty using the Lab and with exploring and applying new scientific visualization strategies, algorithms, and tools to their research. 
• Keeps abreast of emerging visualization solutions.
• Engages the community of researchers involved in computational image analysis across application areas (e.g., biology, physics, chemistry, medical physics).
• Develops, tests, and documents scientific software in support of research goals.
• Works with faculty and their research groups to enable them to fully utilize the University’s and national computational resources for their research.

Skills on Resume: 

• Faculty Collaboration (Soft Skills)
• Proactive Problem Solving (Soft Skills)
• Machine Learning Implementation (Hard Skills)
• Data Analysis Pipeline Development (Hard Skills)
• Visualization Lab Support (Soft Skills)
• Data Visualization Tool Development (Hard Skills)
• Scientific Visualization Assistance (Soft Skills)
• Emerging Visualization Solutions Awareness (Hard Skills)

Job Summary: 

• Implement and develop methods for processing 3D datasets, including point clouds and meshes, for feature extraction and environment reconstruction
• Develop data processing pipeline for light fixture characterization device
• Develop design calculators to aid in light fixture deployment
• Work with the software team to ensure data is delivered in a compatible format
• Work with engineering and product teams to understand product structures 
• Develop scalable computational methodologies to identify splice-isoforms and/or neo-antigens specific to a population of cells via bulk and single-cell transcriptomic sequencing integration.
• Identify complementary public data for integrative analysis with proprietary datasets to identify potential antigens for therapeutic intervention.
• Develop interactive cloud-based tools for ease of viewing and access for single-cell datasets, including splice junctions.
• Propose and analyze new data types (e.g., mass spectroscopy) to identify post-translational modifications and relate inferences to transcriptomic sequencing data.
• Work collaboratively with experimental (wet-lab) teams to prioritize and test identified bioinformatic hypotheses.

Skills on Resume: 

• 3D Data Processing Methods (Hard Skills)
• Data Processing Pipeline Development (Hard Skills)
• Design Calculator Development (Hard Skills)
• Software Team Collaboration (Soft Skills)
• Product Structure Understanding (Soft Skills)
• Computational Methodologies for Transcriptomics (Hard Skills)
• Integrative Data Analysis (Hard Skills)
• Cloud-Based Tool Development (Hard Skills)

Job Summary: 

• Analyze large-scale omics datasets, interpret and communicate analysis results to stakeholders
• Integrate diverse types of biological data to identify leads for trait improvement
• Work closely with other computational scientists and trait scientists to help interpret data and generate hypotheses on how candidate gene function impacts traits of interest
• Contribute to the design of strategies for validating the function of candidate genes
• Provide consultations on experimental design, analytical methods, computational tools, and data interpretation
• Reaching beyond standard functional genomics approaches, explore new machine learning-based approaches for lead identification
• Report research findings (oral and written) at internal, local and national meetings.
• Independently lead computational projects, and contribute to written grants and manuscripts.
• Impact clinical and scientific research projects by designing complex technical programs and applications tailored to define leukemic and immune co-evolutionary states (for example) that influence patient outcomes.
• Analyze, develop and assist others in the development of formalisms, algorithms and software for complex applications, especially regarding intercellular interactions in silico.

Skills on Resume: 

• Large-Scale Omics Data Analysis (Hard Skills)
• Biological Data Integration (Hard Skills)
• Data Interpretation and Hypothesis Generation (Soft Skills)
• Candidate Gene Function Validation Strategies (Hard Skills)
• Experimental Design Consultation (Soft Skills)
• Machine Learning-Based Approaches Exploration (Hard Skills)
• Research Findings Reporting (Soft Skills)
• Computational Project Leadership (Soft Skills)

Job Summary: 

• Develop/modify/create pipelines for interpreting data from single-cell (and/or bulk data) experiments from publicly available and locally developed tools.
• Develop and maintain software tools and infrastructure for resolving specific problems.
• Independently design computational experiments, analysis approach and results interpretation.
• Analyze high-dimensional data from high-throughput profiling technologies (bulk and single-cell) such as whole exome sequencing and a range of single-cell approaches (e.g. RNA/TCR/ATAC/CITE-seq).
• Remain up-to-date on immunogenomic tools.
• Take responsibility for ensuring data organization.
• Advise and assist users and other personnel in analyzing, defining and resolving computer problems.
• Assist in the development, testing and revision of programs.
• Assist in applying advanced statistical methods, simulation models, and skilled programming
• Prioritize and manage multiple projects in a timely and resource-effective manner.

Skills on Resume: 

• Pipeline Development for Data Interpretation (Hard Skills)
• Software Tools and Infrastructure Maintenance (Hard Skills)
• Computational Experiment Design (Hard Skills)
• High-Dimensional Data Analysis (Hard Skills)
• Immunogenomic Tools Knowledge (Hard Skills)
• Data Organization Responsibility (Soft Skills)
• User Support and Problem Resolution (Soft Skills)
• Advanced Statistical Methods Application (Hard Skills)

Job Summary: 

• Develop and design chemical property estimation algorithms using Quantitative Structure-Activity Relationships (QSARs) to elucidate hazard and risk profiles
• Update and enhance knowledge management applications for CBRN purposes
• Review and curate datasets for incorporation into models and tools
• Apply data science practices in the calculation and evaluation of statistical measures
• Build and expand CBRN databases
• Create modeling and simulation tools and web applications
• Perform software development and integration within an agile development process
• Support software lifecycle activities to include requirements development, software design, development, testing, and documentation
• Participate in software design and code reviews to ensure the delivery of quality products and enhance skill sets
• Plan and conduct software tests

Skills on Resume: 

• QSAR Algorithm Development (Hard Skills)
• Knowledge Management Application Enhancement (Hard Skills)
• Dataset Review and Curation (Hard Skills)
• Data Science Practices Application (Hard Skills)
• CBRN Database Expansion (Hard Skills)
• Modeling and Simulation Tool Creation (Hard Skills)
• Agile Software Development (Hard Skills)
• Software Testing and Documentation (Hard Skills)

Job Summary: 

• Define and develop analysis pipelines for scRNAseq data for T cell therapeutics.
• Apply rigorous statistical methods to drive actionable insights from internal and external datasets.
• Build data visualization and exploration tools.
• Collaborate with a diverse team of experimentalists, computational scientists, and clinicians to address key therapeutic questions in a data-centric manner.
• Build machine learning models based on genomic, biological, and clinical features to predict T-cell treatment outcome
• Build machine learning models with scRNAseq data to classify the quality of engineered T cells
• Explore public databases to understand the patient population landscape
• Work with computational scientists, data scientists, engineers, software developers, and geoscientists across the globe to develop, deliver and apply computational tools, models, or software to support business
• Enhance novel proprietary computational models and tools to address evolving business needs
• Use domain knowledge and subject-specific models (Eg. physics-based) – to solve science, engineering, and commercial problems and provide business insights

Skills on Resume: 

• RNA-Seq Data Analysis Pipeline Development (Hard Skills)
• Rigorous Statistical Methods Application (Hard Skills)
• Data Visualization Tool Building (Hard Skills)
• Team Collaboration (Soft Skills)
• Machine Learning Model Development for Treatment Outcome (Hard Skills)
• Machine Learning Model Development for T Cell Quality (Hard Skills)
• Public Database Exploration (Hard Skills)
• Computational Tool and Model Enhancement (Hard Skills)

Job Summary: 

• Whole-genome sequencing, bulk and single-cell RNA sequencing, and bulk and single-cell TCR sequencing of tumor and/or blood samples
• Integrating diverse research and clinical datasets generated from patient samples using different platforms and techniques
• Studies of resistance to existing and emerging cancer therapies using patient-derived data
• Studies of tumor evolution and progression and how it relates to the tumor-immune microenvironment using longitudinal patient samples
• Studies of cancer immunotherapies to develop predictors of response
• Support and conduct research within a translational and clinical research environment that involves curating and storing multidisciplinary data.
• Develop an understanding of cancer biology and cancer immunology key mechanisms
• Design, build and execute studies using proprietary or commercial tools to provide insights including calibrating models to field data and providing field optimization recommendations
• Lead and contribute to manuscript preparation as well as internal and external project-team reports
• Actively participating in project team and group meetings

Skills on Resume: 

• Whole-genome and RNA Sequencing (Hard Skills)
• Data Integration from Diverse Platforms (Hard Skills)
• Resistance Studies Using Patient-Derived Data (Hard Skills)
• Tumor Evolution and Progression Studies (Hard Skills)
• Cancer Immunotherapy Response Prediction (Hard Skills)
• Translational and Clinical Research Support (Hard Skills)
• Cancer Biology and Immunology Understanding (Hard Skills)
• Study Design and Execution (Hard Skills)

Job Summary: 

• Formulate research questions, design experimental protocols, collect data, analyze it, and communicate specific recommendations for how to use the results to improve product
• Review the literature to distill the gold standard measures for complex latent variables including cognitive skills and personality traits
• Translate those gold-standard laboratory paradigms into engaging and rewarding games, surveys, and other activities
• Identify specific gameplay elements in off-the-shelf games that might be able to measure variables of interest to users, then run experiments to put them to the test
• Write production code to process gameplay telemetry and other user data using the scientific Python ecosystem (Numpy, Statsmodels, Pandas, etc.)
• Work with the founding team to develop the overall product strategy and roadmap
• Collaborate with outside experts, corporate customers, and users on how the product can best support assessment and personalized learning and development at scale
• Integrating data across formats and sources by robust synchronization with existing datasets and databases
• Under general direction, developing innovative analytical methods to enable collaborators to interpret and design follow-up research
• Develop analytical methodologies into software tools that will be widely distributed and shared with the scientific community accessing data sets

Skills on Resume: 

• Research Question Formulation and Experimental Design (Hard Skills)
• Literature Review for Gold Standard Measures (Hard Skills)
• Translation of Paradigms into Games and Surveys (Hard Skills)
• Gameplay Element Identification and Testing (Hard Skills)
• Production Code Writing for Data Processing (Hard Skills)
• Product Strategy and Roadmap Development (Soft Skills)
• Collaboration with Experts and Users (Soft Skills)
• Data Integration and Synchronization (Hard Skills)

Job Summary: 

• Applying in-house and commercial simulation tools to formulation processes including granulation, blending, and tableting among others.
• Developing numerical modeling and simulation tools with rigorous validation of the models.
• Delivering high-quality data within defined timelines and aligned with current industry expectations.
• Completing process sensitivity analysis, for example, digital design of experiments and rapid root cause analysis and summarizing results in a technical report.
• Collaborating with internal and external stakeholders to evaluate state-of-the-art modeling tools and develop new solutions.
• Research available methods for time-of-flight diffraction experiments
• Extend the DIALS diffraction analysis software for the processing of single crystal diffraction data from the ISIS pulsed neutron source
• Make the resulting neutron diffraction analysis software available within the Mantid package
• Plan efforts in broad mathematical uncertainty quantification modeling and GPU code-optimization and the relevant library areas of considerable novelty and importance where precedents are lacking.
• Stay abreast of new computational or mathematical technology or library developments to be able to recommend changes in the emphasis of computational programs or new programs warranted by such developments.
• Provide timely and accurate advice to other computational physicists who consult with the successful candidate

Skills on Resume: 

• Simulation Tool Application (Hard Skills)
• Numerical Modeling and Validation (Hard Skills)
• High-Quality Data Delivery (Hard Skills)
• Process Sensitivity Analysis (Hard Skills)
• Stakeholder Collaboration (Soft Skills)
• Time-of-Flight Diffraction Method Research (Hard Skills)
• Diffraction Analysis Software Extension (Hard Skills)
• Mathematical Uncertainty Quantification (Hard Skills)