Computational Geometer Jobs

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE Dynamically managing portfolio risk by evaluating historical and real-time strategy performance. Overseeing automated trade execution and monitoring transaction costs. Supervising a small team of researchers and developers on a daily basis. Designing, researching, and managing sophisticated investment strategies by creating and engineering advance quantitative financial computer modeling systems to aid in analysis and research. Performing research to acquire historical and production data sources needed to build investment models. Designing and developing quantitative mathematical algorithms to link the diverse data sets from various providers. Engineering investment models that will make the buy and sell recommendations for the portfolios using advanced quantitative mathematic statistics and investment theory to design and program strategies that explicitly forecast risk, return, and trading costs. Using quantitative models to value securities. Conducting ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets. Developing aspects of successful statistical models, focusing on forecasting and optimization. Expanding trading universe and volume and expanding to other exchanges and products. REQUIREMENTS Advance degree (Masters or Ph.D.) in a computational or analytical field. Minimum of 10 years’ experience developing, researching or implementing quantitative models for equities, futures and/or FX. Hands on experience with all aspects of the research process, including methodology section, data collection and analysis, testing,

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE Dynamically managing portfolio risk by evaluating historical and real-time strategy performance. Overseeing automated trade execution and monitoring transaction costs. Supervising a small team of researchers and developers on a daily basis. Designing, researching, and managing sophisticated investment strategies by creating and engineering advance quantitative financial computer modeling systems to aid in analysis and research. Performing research to acquire historical and production data sources needed to build investment models. Designing and developing quantitative mathematical algorithms to link the diverse data sets from various providers. Engineering investment models that will make the buy and sell recommendations for the portfolios using advanced quantitative mathematic statistics and investment theory to design and program strategies that explicitly forecast risk, return, and trading costs. Using quantitative models to value securities. Conducting ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets. Developing aspects of successful statistical models, focusing on forecasting and optimization. Expanding trading universe and volume and expanding to other exchanges and products. REQUIREMENTS Advance degree (Masters or Ph.D.) in a computational or analytical field. Minimum of 10 years’ experience developing, researching or implementing quantitative models for equities, futures and/or FX. Hands on experience with all aspects of the research process, including methodology section, data collection and analysis, testing,

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE Dynamically managing portfolio risk by evaluating historical and real-time strategy performance. Overseeing automated trade execution and monitoring transaction costs. Supervising a small team of researchers and developers on a daily basis. Designing, researching, and managing sophisticated investment strategies by creating and engineering advance quantitative financial computer modeling systems to aid in analysis and research. Performing research to acquire historical and production data sources needed to build investment models. Designing and developing quantitative mathematical algorithms to link the diverse data sets from various providers. Engineering investment models that will make the buy and sell recommendations for the portfolios using advanced quantitative mathematic statistics and investment theory to design and program strategies that explicitly forecast risk, return, and trading costs. Using quantitative models to value securities. Conducting ongoing, cutting-edge quantitative research and analysis to enhance existing strategies and to expand into new markets. Developing aspects of successful statistical models, focusing on forecasting and optimization. Expanding trading universe and volume and expanding to other exchanges and products. REQUIREMENTS Advance degree (Masters or Ph.D.) in a computational or analytical field. Minimum of 10 years’ experience developing, researching or implementing quantitative models for equities, futures and/or FX. Hands on experience with all aspects of the research process, including methodology section, data collection and analysis, testing,

Natera is seeking a Bioinformatics Scientist to join our Bioinformatics Research & Development team with a focus on cancer recurrence monitoring. Natera’s mission is to change the management of disease worldwide with a focus on reproductive health, cancer, and organ transplantation. The ideal candidate should have experience in sequencing data analysis, genomics, and/or algorithm development. This individual will analyze large and complex high-throughput cancer genomics datasets. They will also assist in developing novel computational methods, and integrating frameworks developed by our R&D team. PRIMARY RESPONSIBILITIES: Analyze high-throughput DNA sequencing datasets utilizing understanding of cancer biology and genomics. Help implement and validate novel algorithms and statistical methods. Collaborate with molecular biologists and other bioinformatics scientists to answer biological questions Contribute to experimental design and quality control Help develop tools and end-to-end bioinformatics pipelines QUALIFICATIONS: Bachelor's degree in bioinformatics, computational biology, computer science, engineering, molecular biology, or a related field; Master's degree preferred Minimum of 2 years of hands-on experience doing high-throughput genomic sequencing analysis KNOWLEDGE, SKILLS, AND ABILITIES: Experience doing NGS data analysis (e.g. mapping, variant calling, etc.) Strong programming skills in a scientific programming language, Python strongly preferred Knowledge of genomics, with a preference for familiarity with cancer biology Familiarity with public databases such as TCGA, COSMIC, or OncoKB Experience with Linux command-line tools and shell scripting Ability to conduct hypothesis-driven research, visualize data, and effectively communicate results Ability to collaborate effectively, self-motivated, and detail-oriented PREFERRED SKILLS: Background in ML and statistics Experience with WGS Compensation & Total Rewards This range reflects a goo

Natera is seeking a Bioinformatics Scientist to join our Bioinformatics Research & Development team with a focus on cancer recurrence monitoring. Natera’s mission is to change the management of disease worldwide with a focus on reproductive health, cancer, and organ transplantation. The ideal candidate should have experience in sequencing data analysis, genomics, and/or algorithm development. This individual will analyze large and complex high-throughput cancer genomics datasets. They will also assist in developing novel computational methods, and integrating frameworks developed by our R&D team. PRIMARY RESPONSIBILITIES: Analyze high-throughput DNA sequencing datasets utilizing understanding of cancer biology and genomics. Help implement and validate novel algorithms and statistical methods. Collaborate with molecular biologists and other bioinformatics scientists to answer biological questions Contribute to experimental design and quality control Help develop tools and end-to-end bioinformatics pipelines QUALIFICATIONS: Bachelor's degree in bioinformatics, computational biology, computer science, engineering, molecular biology, or a related field; Master's degree preferred Minimum of 2 years of hands-on experience doing high-throughput genomic sequencing analysis KNOWLEDGE, SKILLS, AND ABILITIES: Experience doing NGS data analysis (e.g. mapping, variant calling, etc.) Strong programming skills in a scientific programming language, Python strongly preferred Knowledge of genomics, with a preference for familiarity with cancer biology Familiarity with public databases such as TCGA, COSMIC, or OncoKB Experience with Linux command-line tools and shell scripting Ability to conduct hypothesis-driven research, visualize data, and effectively communicate results Ability to collaborate effectively, self-motivated, and detail-oriented PREFERRED SKILLS: Background in ML and statistics Experience with WGS The pay range is listed and actual compensation packages are bas

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description We are seeking a talented and highly motivated Data Scientist for our Advanced Analytical Technologies team within the Analytical Development organization. The Data Scientist will research, develop, and operationalize advanced machine learning and statistical solutions that improve analytical development across Pharmaceutical Development and Manufacturing. This role will translate scientific and business challenges into scalable, data-driven applications spanning quantitative analytics, predictive modeling, computer vision, and other advanced computational methods. The individual will collaborate with lab scientists, data scientists, engineers, and project managers to deliver robust solutions,

We are hiring senior engineers to work on the CUDA driver, a core component of our platform for accelerating general purpose computation on the GPU. Our team delivers features and improvements to better realize the potential of NVIDIA hardware for a growing range of computational workloads, ranging from deep learning, scientific computation, and self-driving cars to video games and virtual reality! CUDA defines a unified programming model across a range of system configurations and hardware capabilities. To accomplish this, the CUDA driver interacts with GPU hardware, kernel mode drivers, switches and the operating system. What you'll be doing: As a member of our team, you will use your design abilities, coding expertise, and creativity to deliver the best Compute platform in the world. You will craft elegant solutions to exciting problems and craft the future direction of CUDA as you collaborate with your peers across NVIDIA. You will evangelize, architect, and implement new CUDA features You'll oversee and drive development efforts across multiple teams Collaborate with members of hardware architecture teams Help define forward-looking improvements to the CUDA APIs and programming model Design and maintain performance and precision modeling Write effective, maintainable, and well-tested code Develop code for multiple operating systems What we need to see: Bachelor of Science or Master of Science degree in Computer Science, Electrical Engineering, or related field (or equivalent experience) 15&#43; years of relevant systems software development experience Strong C programming skills </

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers, focusing on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimization. What You'll Be Doing: Contribute to the development of open-source inference frameworks such as SGLang and vLLM, including feature and operator development, performance optimization, and model support, in collaboration with the community. Develop and optimize KV cache offloading frameworks for LLM workloads, supporting multi-level cache offloading and reuse across CPU, SSD, and remote storage to improve inference efficiency. (Team project: FlexKV) Drive R&D on compute performance in distributed training, and explore methods and technologies for performance optimization. Study computational challenges in machine learning systems, identify common needs and bottlenecks, and build example code, acceleration libraries, or frameworks accordingly. What We Need to See: Over 5 years working experience in the technology industry, with master’s degree or above in computer science, mathematics, electrical engineering, automation, or related fields. Strong interest in accelerated computing, parallel computing, and heterogeneous computing, with the motivation to explore these areas in depth. Solid programming skills, with a good understanding of data structures and computer systems fundamentals. Strong learning agil

RDQ127R59 Summary As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers. Impact You Will Have Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques. Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks. Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency. Scale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale Innovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments. Minimum Qualifications Education: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc). ML Experience: Strong background in building, training, and deploying machine learning models in production. Infrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks. Core Coding: Proficiency in Python, Scala, or Java. Preferred Skills Advanced Education: PhD in AI, Data Science, or a related technical discipline. Industry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment. Systems Domain:

Become a part of our caring community The Telephonic Quality Outreach Professional supports the EPSDT program requirements in a telephonic outreach environment by evaluating member needs and helping families achieve or maintain an optimal state of wellness. The Telephonic Outreach Care Coach Professional 1 performs basic administrative/clerical/operational/customer support/computational tasks. Typically work on straightforward moderate complexity assignments that are routine and structured in nature. The Telephonic Quality Outreach Professional employs a variety of strategies and techniques to coordinate services and resources that facilitate HEDIS gap closure and improve pediatric health outcomes. The supervisor limits decisions to defined parameters around work expectations, quality standards, priorities and timing, and supervises closely and/or works within established policies/practices and guidelines with minimal opportunity for deviation. Position Responsibilities: Telephonic outreach to close HEDIS gaps for Medicaid pediatric population Assist members in addressing barriers to care, including scheduling challenges and transportation needs, to support access to primary care and overall well-being Collaborate with EPSDT Senior Quality Improvement Professional and Coordinator related to strategic outreach to maximize HEDIS outcomes Collaborate with other departments Provide vaccine awareness and education following Bright Futures and EPSDT preventive health guidelines Empower member independence through education and outreach that promote ongoing self-sufficiency in managing preventive and primary care needs Other responsibilities as assigned Use your skills to make an impact Required Qualifications Unrestricted Licensed Practical Nurse (LPN) in

Use Your Power for Purpose At Pfizer, our purpose is to deliver breakthroughs that transform patients' lives. Central to this mission is our Research and Development team, which strives to convert advanced science and cutting-edge technologies into impactful therapies and vaccines. Whether you are engaged in discovery sciences, ensuring drug safety and efficacy, or supporting clinical trials, your role is crucial. You will leverage innovative design and process development capabilities to expedite the delivery of top-tier medicines to patients globally. Role Summary Pfizer’s Machine Learning and Computational Sciences (MLCS) group is seeking a Senior Machine Learning Scientist to lead independent and collaborative research in computational antibody design and optimization. This position focuses on developing and applying modern computational and machine-learning approaches to accelerate the discovery of next-generation biologic therapeutics. Positioned at the intersection of machine learning, protein science, and therapeutic discovery, the role is ideal for candidates eager to translate foundational AI research into real-world drug design. It offers the opportunity to join an innovative, collaborative environment that supports professional growth through mentorship, knowledge sharing, and the freedom to pursue impactful science. What You Will Achieve In this role, you will: Conduct original research in computational antibody engineering, with an emphasis on sequence- and structure-based generative modeling. Develop and deploy state-of-the-art machine-learning methods for multi-objective, constraint-aware antibody optimization that balances affinity, stability, and developability. Apply proprietary computational frameworks and machine-learning models to predict antibody developability and affinity. Leverage NGS-derived antibody repertoires to info

Senior Low Observables Design & Integration Engineer - Pole Model Company: The Boeing Company Come join a winning team and support the development of Boeing’s Next Generation Air Dominance (NGAD) platforms. The Boeing Defense, Space & Security (BDS) - Phantom Works organization is seeking a Senior Low Observables (LO) Design & Integration Engineer to lead design and analysis activities supporting the fabrication and test of an RCS pole model. The successful candidate will apply deep expertise in LO materials, integration, manufacturing, computational electromagnetic (CEM) modelling, and test support to design, build and test a representative pole model for an advanced next generation program in the St. Louis region. Key Responsibilities: Lead detailed LO design and integration for the RCS pole model, including material selection, incorporation of advanced technologies, supplier hardware integration. Use computational electromagnetic solvers to model, analyze, and optimize radar cross section (RCS) and scattering behavior across required frequency bands and aspect angles in support of pre-test predictions and diagnostics. Work with Manufacturing to ensure proper alignment between design, analysis and fabrication of LO components. Define and support fabrication processes, QA checks, and build plans for LO skins, coatings, RAM treatments, and attachments; identify and mitigate manufacturability risks, provide LO liaison support to the shop. Develop and execute test plans for RCS characterization (anechoic chamber and outdoor ranges), including instrumentation, calibration, and measurement repeatability considerations. Prepare and execute data processing workflows to reduce, calibr

Experienced Low Observables Design & Integration Engineer Company: The Boeing Company Come join a winning team and support the development of Boeing’s Next Generation Air Dominance (NGAD) platforms. The Boeing Defense, Space & Security (BDS) - Phantom Works organization in St. Louis, Missouri , is seeking an Experienced Low Observables (LO) Design and Integration Engineer to support design, analysis, and propulsion subsystem integration of low-observable materials, treatments, and architectures. The ideal candidate will have hands-on experience with LO materials and technologies, demonstrated experience integrating LO solutions with advanced propulsion systems, strong understanding of electromagnetic (EM) principles affecting radar cross section (RCS) and signature, and practical experience using computational electromagnetic (CEM) solvers to design, predict, and optimize low observable systems. Key Responsibilities: Perform design, analysis, and integration activities for LO integration of the propulsion subsystem into an advanced next generation platform, including inlets, nozzle/exhaust, and airframe interfaces Use CEM solvers to model and analyze RCS, scattering, and signature behavior; iterate designs to meet LO requirements Apply electromagnetic theory to assess materials, shapes, and structural features that affect signature across relevant frequency bands Define and execute test plans and validation activities (lab and range) to verify LO performance and support correlation between simulation and measurement Collaborate with multidisciplinary teams (structures, propulsion, materials, flight test, systems engineering, producibility) to ensure integrated solutions meet pe

Experienced Low Observables Mission Systems Integration Engineer Company: The Boeing Company Come join a winning team and support the development of Boeing’s Next Generation Air Dominance (NGAD) platforms. The Boeing Defense, Space & Security (BDS) - Phantom Works organization is seeking a highly skilled and experienced Low Observables Mission Systems Integration Engineer to support an integrated product team in the design and integration of an advanced sensor for a next generation platform. The ideal candidate will have a strong background in low observable technologies and systems integration, with a focus on antennas, apertures, and radomes. This role requires technical leadership and collaboration across various engineering disciplines to ensure the successful integration of low observable sensors. Key Responsibilities: Lead the integration of a low observable sensor, ensuring compliance with design and performance requirements Collaborate with a cross-functional team to develop and implement integration strategies for a critical platform sensor Utilize computational electromagnetic solvers to analyze and optimize low observable designs Provide technical leadership and mentorship to engineering teams, fostering a culture of innovation and excellence Oversee the design and integration of low observable sensors, ensuring alignment with program objectives and timelines Stay current with advancements in low observable materials and technologies, applying this knowledge to enhance system performance Basic Qualifications (Required Skills and Experience): ​ ​ Bachelor of Science degree in Engineering (with a focus in Electrical, Mechanical or

Senior Low Observables (LO) Mission Systems Integration Engineer Company: The Boeing Company The Senior LO Mission Systems Integration Engineer will lead design, integration, analysis, test, and production activities for low observable materials, structures, apertures, sensors, and radomes for mission systems. The role requires strong technical leadership, independent execution of complex tasks, advanced use of computational electromagnetic (CEM) solvers, and the ability to produce and defend technical results with minimal oversight. Key Responsibilities Lead design, modeling, and analysis efforts for LO materials, coatings, structures, and integrated mission systems to meet signature reduction and performance requirements. Independently apply CEM solvers (e.g., FEKO, HFSS, CST, WIPL‑D, xFDTD, or equivalent) to model antennas, apertures, radomes, and LO treatments; perform design optimization and trade studies. Drive integration of LO treatments with mechanical, thermal, and sensor/antenna system constraints; identify and mitigate producibility, testability, and sustainment risks. Plan, execute, and oversee laboratory and field tests (anechoic chamber measurements, antenna/radome characterization, RCS measurements); lead data collection, reduction, and validation activities. Develop and validate predictive models, reconcile simulations with measurements, perform uncertainty quantification, and provide actionable recommendations to engineering and program leadership. Produce high-quality technical documentation: test plans, test reports, technical memoranda, design reviews, and customer briefings. Mentor and provide technical oversight to junior engineers and technicians; ensure adherence to engineering processes, qual