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Xerox Research Scientist, Design Optimization in North Carolina

Research Scientist, Design Optimization

General information

City: Palo Alto, Cary

State/Province: California, North Carolina

Country: United States

Department: Research & Development

Date: Friday, March 5, 2021

Working time: Full-time

Ref#: 20010728

Job Level: Individual Contributor

Job Type: Experienced

Job Field: Research & Development

Description & Requirements

PARC, a Xerox company, is in the Business of Breakthroughs®. Practicing open innovation, we provide custom R&D services, technology, expertise, best practices, and intellectual property to Fortune 500 and Global 1000 companies, startups, and government agencies and partners. We create new business options, accelerate time to market, augment internal capabilities, and reduce risk for our clients. Since its inception, PARC has pioneered many technology platforms – from the Ethernet and laser printing to the GUI and ubiquitous computing – and has enabled the creation of many industries. Incorporated as an independent, wholly owned subsidiary of Xerox in 2002, PARC today continues the research that enables breakthroughs for our clients' businesses.

PARC is seeking a Research Scientist with deep expertise in generative design, shape/topology and material layout optimization, and solid/fluid mechanics. The ideal candidate will have strong fundamental (theoretical and computational) background, mathematical and algorithmic skills, implementation skills, and experience formulating problems and developing principled solutions. The Research Scientist will work on ongoing projects funded by Xerox, government agencies (e.g., DARPA, ARPA-E, and NIST), national labs and industrial partners, on a range of topics including digital design and manufacturing software and hardware technologies, process modeling and simulation, hybrid (additive and subtractive) manufacturing, design for assemblies, design for manufacturing, and physics-informed AI. The candidate must be comfortable and experienced with 3D design and optimization, physics-based analysis (e.g., finite element/volume methods), sensitivity analysis, design under uncertainty, and their application to design of mechanical systems. Familiarity with any of dynamic nonlinear systems modeling and design, multi-body kinematics and dynamics, mechanism design, statistics and probabilistic modeling, machine learning, computational material science, and manufacturing analysis are a plus.

In the short-term, the projects will require developing shape/topology and material layout optimization algorithms for multi-physics performance (e.g., thermoelastic behavior), various manufacturing constraints, and architected material structures. Responsibilities may include one or more of the following: Developing gradient-descent optimization algorithms for parametric and volumetric representations, developing multi-scale and probabilistic material models, using open-source numerical simulation packages (e.g., MFEM or FEniCS), developing ML-based surrogate models, formulating sensitivity measures for various design constraints, and coupling part- and assembly-level design iterations. Longer-term expectations include generating impactful publications and high-value intellectual property, developing strong proposals for internal and external funding, leading interns and junior researchers, establishing a research program, and contribute to the long-term strategy for computational design research at PARC.

Responsibilities:

  • Participating in fundamental and applied research, including mathematical formulation, analytical or numerical solutions, and validation.

  • Leading or contributing to conference and/or journal papers, invention disclosures, white papers, research proposals, and presentations to internal and external stakeholders.

  • Implementing good-quality computer code (research-grade software prototypes).

  • Supporting software engineers in transforming research prototypes into commercial-strength products.

Requirements:

  • Ph.D. in Mechanical Engineering, Electrical Engineering, Physics, Applied Math, Computer Science/Engineering, or related discipline.

  • At least four years of academic research experience as a Graduate/Research Assistant in an ongoing higher-education (Master’s or Ph.D.) program.

  • Demonstrated expertise in generative design and shape/topology optimization.

  • Strong understanding of optimization theory, numerical analysis, computational mechanics, and computational geometry.

  • Familiarity with at least one programming language (e.g., Python or C++)

  • Familiarity (or ability to quickly learn) open-source physics-based simulation platforms (e.g., MFEM or FEniCS).

  • Demonstrated experience with research-grade publications and strong track record as a first author in high-quality peer-reviewed journals or conferences.

Desirable Technical Skills:

  • Having one year of additional postdoctoral research experience in a related field is highly preferred, but not required for excellent candidates.

  • Related industrial, corporate, or entrepreneurial experience is a plus but not required.

  • Experience with additive manufacturing or energy management systems is a plus.

  • Experience with parallel computing (CPU/GPU), computational or experimental material science, machine learning, or probabilistic modeling is a plus.

Desirable Personal Skills:

  • Independence in problem formulation and creativity in problem solving.

  • Attention to detail and ability to manage multiple projects simultaneously.

  • Eagerness to learn new technologies and applying fundamental research to solve real-world problems with commercial potential.

  • Strong organizational and inter-personal skills.

  • Strong communication (oral and written) skills.

Candidates are encouraged to upload (a) a one-page research statement outlining their research accomplishments, current activities, and future directions; (b) a technical writing sample (e.g., a first-authored paper); and (c) a letter of recommendation from a technical supervisor.

Xerox is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, creed, religion, ancestry, national origin, age, gender identity or expression, sex, marital status, sexual orientation, physical or mental disability, use of a guide dog or service animal, military/veteran status, citizenship status, basis of genetic information, or any other group protected by law. Learn more at www.xerox.com and explore our commitment to diversity and inclusion! (https://www.xerox.com/en-us/jobs/diversity) People with disabilities who need a reasonable accommodation to apply or compete for employment with Xerox may request such accommodation(s) by sending an e-mail to XeroxStaffingAdminCenter@xerox.com. Be sure to include your name, the job you are interested in, and the accommodation you are seeking.

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