Virginia Mountain View

Research Scientist

  • 531639
  • Blacksburg, Virginia, United States
  • Electrical and ComputerEngineering
  • Engineering
  • Research / Scientific
  • Research Faculty
  • Virginia Tech

Job Description

Research Scientist working under the supervision of Professor (Dr.) Leonard Smith in ECE at Virginia Tech engages in research and various ongoing research projects related to connected coping with structural model error in prediction of nonlinear dynamic systems and the development of novel communication and pedagogical materials to enhance wider understanding of the limits of current methods and advantages of the alternatives developed. Perform both independent and supervised research under the supervision of the adviser. Conduct research for simulation model development and actual real-time forecasting of laboratory test systems. Read and digest necessary and relevant research articles, applying appropriate classical and contemporary analytical methods to find new techniques/solutions. Write reports, submit deliverables to sponsors, prepare manuscripts based on the research findings and publish on scientific platforms. Work in a collaborative team environment. Assist in supervising graduate and undergraduate students, proposal writing and preparation for potential funding, and other research duties. Develop and contribute ideas for prediction, likely prediction failure, control, education and decision-making. Design and implement some of the most capable and advanced forecasting and decision support software on the planet.

Required Qualifications

- Ph.D. in either Physics or Mechanical/Electrical/Electronics/Control Engineering or Applied Statistics with substantial post-Ph.D.
- Demonstrated experience in one or more of the following areas along with programming skills in MATLAB, C/C++/Python, and ROS, or similar languages for software/algorithm development and hardware/machine interface: autonomous systems; machine learning; data acquisition.
- Excellent communications skills.

Preferred Qualifications

- Significant experience in the application control systems modeling, design, and implementation; signal processing, and sensor fusion.
- Demonstrated expertise and prior work in related areas for instance, Nonlinear Forecasting, collision detection and avoidance, multi-robot coordination via probabilistic forecasting, decision making assistance systems, and man-machine interface.
- Experience in simulator experimentation and web based data extraction.

Appointment Type

Restricted

Salary Information

Commensurate with Experience

Review Date

12/02/2024

Additional Information

The successful candidate will be required to have a criminal conviction check.

About Virginia Tech

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance.  These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are an individual with a disability and desire an accommodation, please contact K Atkins at atkins@vt.edu during regular business hours at least 10 business days prior to the event.

 

Each agency within the Commonwealth of Virginia is dedicated to recruiting, supporting, and maintaining a competent and diverse work force. Equal Opportunity Employer

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