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A leading company is seeking a Principal Scientist to advance intelligent systems in critical domains like defense and healthcare. This role involves driving research, collaborating with experts, and ensuring the trustworthiness of AI systems. Candidates should possess a Ph.D. and a strong research background, with a passion for learning and innovation.
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About Galois
Galois tackles the hardest problems in computer science. Our mission is to assure trust in critical systems that protect the privacy and integrity of information in the real world. Core to this is the application of formal analysis techniques that allow systems to be modeled, analyzed, and mathematically proven correct to ensure that a system behaves exactly as we intend under all circumstances.
About Galois
Galois tackles the hardest problems in computer science. Our mission is to assure trust in critical systems that protect the privacy and integrity of information in the real world. Core to this is the application of formal analysis techniques that allow systems to be modeled, analyzed, and mathematically proven correct to ensure that a system behaves exactly as we intend under all circumstances.
We are a community of researchers, engineers, and operations people who are dedicated to creating trustworthiness in critical systems in every functional area of the organization. Our organization is highly collaborative, and we pursue working from first principles, transparency, building deep trust, learning and innovating, and creating space for you to be authentically you. Our unique organizational structure enables us to adapt to the needs of the innovative projects we deliver.
We are employee-owned and aspire to provide employees with a sense of freedom to pursue passions in and out of work — whether it be opportunities to learn, career growth, a sense of community, or whatever else brings you value as a person.
For more on our organizational structure, visit Life at Galois.
About This Role
We're looking for a new Principal Scientist passionate about expanding intelligent systems' capabilities to join Galois' research team. Our clients are looking at us to significantly advance the state-of-the-art in designing and deploying solutions that operate in challenging safety-critical domains ranging from defense to healthcare to aviation, specifically focusing on formally establishing and ensuring the trustworthiness and safety of these systems during operation.
We're hiring a Principal Scientist passionate about pushing the boundaries of ensuring AI systems' trustworthiness, safety, and reliability. In this role, you will drive a research agenda and develop R&D opportunities that involve engaging with customers to help solve real-world problems where the stakes are high. You will have the opportunity to collaborate with a multidisciplinary team of experts in algorithm design, mathematics, cognitive science, engineering, and psychology. Our objective is to perform rigorous research on AI systems focused on establishing their performance and trustworthiness in real-world contexts and by actual human users. Our research is not strictly limited to LLMs and related technologies - we're also investigating a variety of neurosymbolic and hybrid approaches to AI development for our clients, so if you're looking for a supportive atmosphere to trailblaze new ideas and AI frameworks, Galois is the place for you. You will also collaborate extensively with a team of experts in AI/ML, mathematics, cognitive science and engineering to advance the state-of-the-art in this field.
Together, we pursue innovative research that helps our clients build safe, reliable, and trustworthy systems. We're looking for people who can invent, learn, think, and inspire colleagues and clients. While we are specifically interested in researchers who desire to work on computational mathematics at scale, we are broadly interested in highly motivated researchers in the broad domain of computational mathematics, including computer arithmetic, algorithm analysis, applied probability, combinatorial scientific computing, control theory, data science, data-driven methods, discrete mathematics, discretization methods, graph algorithms, high-performance computing, integral equations and nonlocal models, linear and multilinear algebra, machine learning, mathematical analysis, meshing, modeling & simulation, multilevel/multiphysics/multiscale methods, numerical analysis, operations research, optimization, ordinary and partial differential equations, numerical solvers, statistical inference, time integration, and uncertainty quantification.
Responsibilities
As a Principal Scientist, you will:
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