Student Veterans of America Jobs

Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

Here are a few things you should know:
  • This site is mobile friendly. You do not need a log-in or password to access information.
  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
  • The site is refreshed daily to remove out-of-date content.
  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.

Job Information

North Carolina Agriculture & Technical State Unive Post Doc Research Associate, Autonomous Control and Information Technology Institute in Greensboro, North Carolina

Description:

The primary purpose of the position is to develop data driven methods and implement testing and evaluation techniques for autonomy algorithms of unmanned aerial vehicles.

The position is a non-tenure-track with a year-to-year appointment. This role is renewable annually for up to three years subject to satisfactory performance and the availability of resources, and the needs of the Institute.

In particular, we are looking for applicants with a demonstrated record of accomplishment in data science, unmanned aerial vehicles and have strong background in systems, testing, machine learning and evaluation problem solving.

Demonstrated proficiency in programming skills are required (Preferably Python, C++, Matlab), and practical experiences with micro aerial vehicle such as quadcopter is desired.

It is expected for candidates to have demonstrated/published research products on robotic applications, especially within the experimental setup of perception, localization, path planning, motion planning and navigation problems for both hardware and software implementation.

Desired applicants have experience with simulation software such as Gazebo, or CoppeliaSim(V- REP ) and popular python machine learning libraries including Numpy, Pandas, Bokeh, Tensorflow, PyTorch, scikit-learn etc.

The candidate will work with both graduate and undergraduate students in a mentoring role, and will be involved in developing research proposals, conducting workshops, and seminars.

In particular, they will be conducting research on aerial robotics with either ROS or V- REP operating systems.

The candidate will enjoy a dynamic and collaborative working environment on our cutting-edge autonomous vehicle research team. U.S. citizenship is preferred, but non U. S. citizens are also encouraged to apply.

ABD candidates will also be considered. If interested, please apply electronically and send a detailed curriculum vitae, copies of your top three publications, a summary of your PhD dissertation, names and contact information of three references.

Any, other information that might be relevant to your application is also welcome.

Please forward all required information to ACIT Institute Director Dr. Abdollah Homaifar (homaifar@ncat.edu) for consideration.

This information must be uploaded and attached to your application within “other” document section.

Primary Function of Organizational Unit:

The Autonomous Control and Information Technology ( ACIT ) Institute at NC A&T State University is inviting applicants to submit for a full-time, post-doctoral research associate position in Machine Learning and Unmanned Vehicles.

The project focus is on data driven methods to develop and implement testing and evaluation techniques for autonomy algorithms of autonomous vehicles and it is funded by a project funded NASA ULI .

Internal job number: 009278

Requirements:

PhD in Electrical Engineering, Computer Science, Aerospace or related field

Preferred:

5 years of experience in data driven methodology and testing and evaluation, which will include time to earn the PhD degree.

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