Positions

Simulation Demo Developer (Georgia Tech Student)

 

Job Description

The NSF Artificial Intelligence (AI) Research Institute for Advances in Optimization (AI4OPT) is seeking a motivated and skilled Georgia Tech student to join our team as a Simulation Demo Developer. In this role, you will be responsible for creating simulation demos using programs such as AnyLogic to showcase the capabilities of transportation system analysis and data management.

 

  • Hours/Schedule

    • 10-20 hours per week

  • Location

    • Hybrid/Remote

  • Pay Rate

    • $15/hr

  • Positions Available

    • 1

Responsibilities:

  • Develop simulation demos using AnyLogic to illustrate the functionality and benefits of transportation system optimization.
  • Understand the workings of AnyLogic simulation models and how they enable organizations to effectively manage transportation, maximize loads, minimize risks, and provide detailed analysis.
  • Create simulation models that cover essential processes carried out by distribution centers, including loading, unloading, and order preparation.
  • Collaborate with the AI4OPT team to ensure the accuracy and relevance of the simulation demos.
  • Provide insights and suggestions for improving simulation models and demo presentations.

Requirements:

  • Currently enrolled as a student at Georgia Tech, preferably with a focus on industrial engineering, operations research, or a related field.
  • Familiarity with simulation software such as AnyLogic and demonstrated experience in creating simulation models.
  • Strong understanding of transportation systems and logistics processes.
  • Analytical and problem-solving skills.
  • Ability to work independently and collaborate effectively with team members.
  • Strong communication skills, both written and verbal.
  • Detail-oriented with a commitment to producing high-quality work.

Benefits:

  • Gain valuable hands-on experience in the field of transportation system optimization and simulation.
  • Opportunity to work with a dynamic team of industry professionals and researchers.
  • Flexible schedule to accommodate academic commitments.

 

How to Apply:

If you are interested in joining AI4OPT as a Simulation Demo Developer, please submit your resume to Breon Martin - breon.martin@gatech.edu. Be sure to include examples of any simulation models or projects you have worked on.


Contact Breon Martin

Postdoctoral Fellow / Research Faculty at Georgia Tech

AI4OPT is hiring researchers in AI for Supply Chains at Georgia Tech at the postdoc and research faculty level. Applicants should have obtained a PhD degree and have a background in optimization or AI/ML, and applicants with inter-disciplinary and diverse expertise are encouraged to apply. Both positions require strong technical skills and coding expertise in Python, Julia, or C++.

Successful candidates will contribute to research projects that primarily focus on applying large-scale optimization and machine learning to critical applications in supply chains and manufacturing. Candidates will be part of multi-disciplinary research teams that bring together world leaders in AI and optimization from six universities to work on real problems with real data from the largest supply chains in the world. Candidates will have the opportunity to supervise students and manage projects with partners such as UPS, Ryder, Best Buy, Kinaxis, and Intel.

Successful candidates at the research faculty level will take on a larger responsibility and work directly with the AI4OPT Director to manage the overall supply chain program of the Institute. They will have additional opportunities to develop leadership skills, and will be involved in a variety of research projects. In addition to the postdoc eligibility requirements, this position requires prior leadership experience or research/industry experience after completing the PhD.

AI4OPT is one of the 25 National Artificial Intelligence Research Institutes set up by the National Science Foundation to conduct use-inspired research and realize the potential of AI. The AI Institute for Advances in Optimization (AI4OPT) is focused on AI for Engineering and is conducting cutting-edge research at the intersection of learning, optimization, and generative AI to transform decision making at massive scales, driven by applications in supply chains, energy systems, chip design and manufacturing, and sustainable food systems. AI4OPT brings together over 70 faculty and students from Georgia Tech, UC Berkeley, University of Southern California, UC San Diego, Clark Atlanta University, and the University of Texas at Arlington, working together with industrial partners that include Intel, Google, UPS, Ryder, Keysight, Southern Company, and Los Alamos National Laboratory.

Reach out to Kevin Dalmeijer for more information and to apply. You can also reach out to schedule an in-person meeting at the INFORMS annual meeting in Phoenix.
Contact Kevin Dalmeijer

PhD students at Georgia Tech

Both current and potential PhD students at Georgia Tech and can reach out directly to the contacts below to get involved in AI4OPT research. We especially encourage students early in the program, as the projects are conducted by teams of faculty and students over multiple years. Please share your CV and your research interests when reaching out.

You can also send your CV and research interests to Kevin Dalmeijer for a general application.
Contact Kevin Dalmeijer

End to End Optimization

The thrust aims at establishing the theoretical and computational foundations of end-to-end learning and optimization, and demonstrating its societal values on end-use cases in energy, supply-chains, and circuit design. This includes developing “optimization proxies” for complex optimization problems, i.e., trained ML models that mimic the optimization but are several orders of magnitude faster. Other methodologies that are explored are “learning to optimize” (replace components of an optimization algorithm with a trained ML model) and “end-to-end learning” to effectively address prediction and optimization challenges in tandem, rather than the standard paradigm of predict-then-optimize.
Contact Pascal Van Hentenryck

Logistics and Supply Chains

The COVID-19 pandemic has highlighted the lack of resiliency of existing supply chains and the limitations of the just-in-time paradigm. Supply-chain disruptions led, and continue to lead, to significant delays in major projects, lost sales and, in some cases, significant financial problems. Recently rising inflation has confounded these resiliency issues, indicating the need for appropriate tradeoffs between costs and resiliency. This requires a paradigm shift in supply-chain design and operations. The goals of this thrust include developing the methodologies and algorithms to facilitate this paradigm shift, and to incorporate ML to deliver high-quality solutions to large-scale supply-chain applications in real time.
Contact Pascal Van Hentenryck

Other Projects

The following projects involve Georgia Tech students, but are not actively recruiting at this point.

  • Theoretical Foundations of Ethical AI/OPT
  • Ethical Societal Systems
  • Ethics Standards
  • Uncertainty Quantification for Multi-Stage Optimization
  • Multi-stage Optimization Models and Algorithms
  • Bayesian Risk-Sensitive and Distributionally-Robust Optimization
  • nu-Market: A New Market for Power Systems
  • Resource Adequacy Problem
  • Decentralized Optimization
  • AI for Nutrient Recovery, Membrane Fouling, and Membrane Cleaning
  • AI for CO2 Absorption and CH4 Recovery
  • Fine Cultivation of Crops
  • Circuit Design - Physics-Based Deep Learning for Inverse Optimization of Circuits