Staff Engineer/Materials Modeler in New Kensington, PA at Arconic

Date Posted: 10/10/2018

Job Snapshot

  • Employee Type:
    Full-Time
  • Location:
    100 Technical Drive
    New Kensington, PA
  • Job Type:
  • Experience:
    At least 5 year(s)
  • Date Posted:
    10/10/2018

Job Description

The Staff Engineer will lead Arconic Technology Center’s modeling effort to connect alloy microstructures to material properties and performance.  Design experiments to measure relevant characterization data needed as inputs.  Develop and employ thermodynamic and kinetic models to predict cast structures, phase transformations, precipitation, and particle evolution as a function of solidification conditions and subsequent thermal treatments.  Package distinct modules into a cohesive framework, and summarize results to stakeholders.  Manage the project, including responsibilities for: resources, milestone tracking, and deliverable execution.   

​Major activities/Key challenges:
  • Set the overall project strategy and tactical approach to deliver on-time, on-scope and on-budget.
  • Lead the assembly of component models across different processing stages into one cohesive framework, leveraging advanced numerical toolkits to understand chained material and process models.
  • Develop and test computational and physics-based models relating to microstructural evolution of aluminum alloys and other metals, from casting through fabrication, including additive manufacturing.
  • Develop and test models which connect microstructure to properties, for metals including aluminum, titanium, nickel-based and other alloy systems.
  • Critically assess experimental data used for tuning models; guide future tests of microstructural characteristics.
  • Drive communication between stakeholders;  report on progress and key achievements to senior executives.
  • Accountable for forecasting and financial budgets for projects including internal and external expense.
  • Identify and submit new ideas for Intellectual Property that enable a sustainable competitive advantage for Arconic.
  • Lead alloy and/or process improvement projects aimed at reducing costs, improving recovery, adding revenue, etc. working with business units and other ATC divisions as appropriate

Essential Knowledge & Skills/Education:
  • Knowledge of aluminum-, titanium-, and/or nickel-based alloy physical metallurgy. 
  • Expertise in processing/microstructure/properties relationships in metal systems.
  • Mathematical modeling capabilities, including development, debugging and integration of source code across multiple platforms.
  • Proficiency in the efficient design of R&D experiments to acquire desired outputs. 
  • Data analysis, determination of impact variables and predictions of trends.
  • Demonstrated experience in leading cross-functional teams. 
  • Strong interpersonal skills with team members, work partners, business unit personnel, and external customers.
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Qualifications

Basic Qualifications
  • Ph.D. in Materials Science/Engineering, Metallurgy, Mechanical or Welding Engineering from accredited institution
  • Minimum 5 years' experience in an industrial or laboratory work environment
  • Minimum 5 years’ experience using MatLab. 
  • Minimum 3 years’ experience using CALPHAD models (e.g. Thermo-Calc or Pandat) including precipitation and diffusion modules. 
  • Employees must be legally authorized to work in the United States.  Verification of employment eligibility will be required at the time of hire.  Visa sponsorship is not available for this position.
  • This position is subject to the International Traffic in Arms Regulations (ITAR) which requires U.S. person status.  ITAR defines U.S. person as an U.S. Citizen, U.S. Permanent Resident (i.e. 'Green Card Holder'), Political Asylee, or Refugee. 
Preferred Qualifications
  • Experience designing experiments to determine properties of relevant metals, i.e. aluminum, titanium, and/or nickel-based alloys
  • Application of CALPHAD programs to determine phases present in Al, Ti, Ni alloys as a function of solidification and processing history
  • Data science comprehension, and implementation of machine learning algorithms
  • Programming with R, creating Shiny apps  ;  Experience with mixed language programming