Support the operation, evolution, and adoption of enterprise bioinformatics platforms and analytical tools for public health missions.
Locations (2)
Georgia, United States
United States
Compensation
USD $82,000.00/Yr. Up to USD $92,000.00/Yr.
Responsibilities
Support the day-to-day operation and continuous improvement of enterprise on-premise and cloud-based high performance computing bioinformatics platforms, analytical tools, and data workflows.
Analyze bioinformatics workflows, data types, and analytical use cases to identify operational needs, issues, dependencies, and opportunities for improvement.
Gather, document, and translate scientific, technical, and operational requirements into actionable requirements, user stories, use cases, acceptance criteria, and platform capabilities.
Develop bioinformatics pipelines, databases, and conduct data analysis as required.
Coordinate with bioinformatics, data science, engineering, and cloud and on-premise infrastructure, and other technical teams to support delivery and resolve operational issues.
Lead the development and delivery of innovative applications, data platforms and workflows that support NSW's earth observation, satellite imagery and environmental monitoring programs.
Locations (3)
Grafton, New South Wales, Australia
Parramatta, New South Wales, Australia
Dubbo, New South Wales, Australia
Compensation
Salary relative to experience, and ranges from $148,339 to $163,480 per annum + super
Responsibilities
Lead design, development and deployment of applications on a high-performance computing environment
Work closely with scientists, system administrators and stakeholders to deliver scalable software solutions
Improve data accessibility, strengthen DevOps practices and support critical land use, vegetation and environmental monitoring initiatives
Lead AI strategy, research, and technology roadmap for Micron’s ITP AI organization, driving breakthrough innovations and influencing enterprise-wide AI adoption
Compensation
$255,000.00 - $447,000.00 a year
Responsibilities
Shape long-term AI vision and technology roadmap
Advise executive leadership on AI strategy and investments
Lead AI research initiatives across GenAI, agentic AI, machine learning, scientific AI, semiconductor-focused AI
Champion AI application to engineering productivity, design, manufacturing, and business operations
Influence technical standards and AI platform adoption
Requirements
PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering, Applied Mathematics, or related field
Design, perform, and validate molecular-scale simulations of fluid behavior, transport, and interactions with mineral or organic pore surfaces; analyze implications for petrophysical properties.
Develop and evaluate computational models of nuclear and magnetic-resonance measurements, including applications to subsurface characterization and monitoring in well environments.
Use scientific programming, numerical methods, and high-performance computing resources to manage simulations, assess uncertainty, interpret results, and improve reproducibility.
Integrate computational predictions with available experimental measurements; investigate model sensitivity and interpret scientific findings.
Prepare technical reports, manuscripts, presentations, and research updates; coordinate with faculty, students, collaborators, and consortium sponsors.
Lead a world‑class team advancing cooling and thermal design technologies for high‑temperature aerospace and propulsion components.
Compensation
The base pay range for this position is $130,000 - $240,000 USD USD Annually. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set. This position is also eligible for an annual discretionary bonus based on a percentage of your base salary/ commission based on the plan.
Responsibilities
Lead strategic direction, technical execution, and talent development of GE Aerospace Research's component heat transfer capability
Own a research portfolio spanning cooling design, heat transfer and storage solutions, conjugate heat transfer modeling and simulation, and test and diagnostic capabilities
Partner with Technology Director - ATMS to align strategy with business needs
Lead a diverse team of scientists and engineers
Build culture of action and operational excellence
Requirements
Master's degree in Mechanical Engineering, Aerospace Engineering, or a related engineering discipline with a focus on heat transfer or thermal-fluid sciences
Nice to have: PhD in Mechanical Engineering, Aerospace Engineering, or a related engineering discipline
Nice to have: minimum 8 years of professional experience in research, development, or engineering for aerospace and propulsion applications
Nice to have: minimum 3 years of direct people leadership experience in a research or laboratory environment
The Senior Scientist will advance AI-enabled de novo antibody discovery through iterative design-build-test-learn cycles, combining antibody discovery, structural biology, and computational methods to translate target protein structure into discovery campaigns.
Compensation
The salary range for this position is: $169,320.00 - $219,120.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package.
Responsibilities
Lead de novo antibody discovery and optimization campaigns from target and epitope assessment through design, screening, iteration, and hit selection.
Develop integrated computational and experimental screening strategies for de novo designs, including candidate prioritization, library design, multiplexing, and recombinant and display-based approaches.
Critically evaluate experimental and predicted structural models to prioritize biologically relevant epitopes and guide discovery strategies.
Integrate computational, structural, binding, functional, and developability data to inform campaign iteration and binder advancement decisions.
Rapidly prototype computational workflows that address antibody discovery and optimization needs.
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