R&D Staff Member, Sensors and Embedded Systems Group

Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831
  • Job Type
    Employee
  • Job Status
    Full Time

Purpose

This position focuses on research and development of mechatronic technologies for de-manufacturing.  De-manufacturing is the application of advanced robotics, sensors and control strategies to maximize value recovery from electronic waste streams.  Currently, so called e-wastes can contain large quantities (metric tons) of critical materials such as rare earth permanent magnets, lithium, cobalt, manganese and other desirable materials.  Of a particular interest are innovative strategies for ultra-high throughput processing that can recover valuable sub-assemblies, components and materials.  Recently, ORNL has demonstrated systems that process computer hard drives and electric machines and Li-ion battery stacks with favorable economics because of their processing speed and agility to handle highly variable waste streams.  In particular, mechatronic technology capable of dismantling 1 hard drive every 6 seconds has been demonstrated.

 

The Sensors & Embedded Systems Research (SESR) Group in the Electrical and Electronics Systems Research (EESR) Division at the Oak Ridge National Laboratory (ORNL) is seeking applications for an R&D Staff Member position that will perform research in the area of novel mechatronic systems development including advanced sensors, controls and machine learning.  Emphasis on new or improved de-manufacturing platforms for rapid device dismantlement, customized sensors or measurement technologies that enable specialized applications, and extreme processing environments. The SESR Group develops mechatronics, innovative sensors, embedded systems and microelectronics for myriad applications in order to advance science, address energy challenges, and enhance national security. 

 

Job Duties and Responsibilities

This position will involve the development of novel mechatronic systems with innovative sensors, controls and machine learning technologies and contribute to establishing new critical materials supply chains in the U.S.

As an ORNL core strength, concepts and technologies developed for additive manufacturing can now be leveraged for de-manufacturing concepts that support ORNL/DOE missions in science, energy, and national security. Representative activities include concept development of novel devices and systems, design and fabrication and prototype characterization at the microelectronics level to complete mechatronic systems capable of processing at the pilot commercial scale.  Methods and tools employing advanced manufacturing by standard semiconductor and additive manufacturing methods, device characterization, and experimental evaluation in representative laboratory and field environments. The candidate is expected to have familiarity with standard electro-mechanical technologies (robots, etc.), sensor modalities and their conversion to quantifiable electrical signals by analog and digital signal processing. The candidate should also have a background in technology development from Basic (TRL1) to laboratory prototype (TRL4) and beyond. Familiarity with standard electrical, electrochemical, and optical measurement methods is also desirable.

Requirements

Required Qualifications

  • A master’s or doctoral degree in Electrical Engineering, Mechanical Engineering, Material Science or Physics
  • Experience developing and using mechatronic, sensing, control and machine learning technologies
  • Working knowledge of general laboratory equipment and use including oscilloscopes, function generators, power supplies, spectrum analyzers, etc.
  • Experience and skill writing journal publications and funding proposals a plus
  • Excellent communication skills (oral and written) and strong interpersonal skills
  • Enjoy highly collaborative, teaming environment

 

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.


If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.


ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.

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R&D Staff Member, Sensors and Embedded Systems Group

Oak Ridge National Laboratory
Oak Ridge, Tennessee 37831

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