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Research Assistant, ECECS

Position Type: Federal Work Study or Non-Work Study 


Essential Duties and Responsibilities 

Responsibilities include, but are not limited to the following: 

As a Research Assistant in the field of Machine Learning-Based Indoor Localization, your responsibilities will include:


Data Collection and Preprocessing:

  • Collecting Wi-Fi RSSI (Received Signal Strength Indicator) fingerprints in various indoor environments using appropriate tools and equipment.
  • Organizing and cleaning collected data to ensure accuracy and consistency.


Data Annotation and Labeling:

  • Annotating collected data with ground truth location information for training and evaluation purposes.


Algorithm Development:

  • Assisting in the development and optimization of machine learning algorithms for indoor localization based on Wi-Fi RSSI data.
  • Conducting experiments to evaluate the performance of different algorithms and fine-tuning parameters.


Literature Review:

  • Conducting literature reviews to stay up-to-date with the latest research in the field of indoor localization and machine learning.



  • Documenting research methodologies, findings, and experimental results in an organized and clear manner.
  • Preparing reports, presentations, and visualizations to communicate research progress.



Minimum Qualifications:

  • Enrollment in a relevant undergraduate or graduate program, such as Computer Science, Electrical Engineering, or a related field.
  • Strong interest in machine learning, wireless communication, and indoor positioning systems.
  • Knowledge of programming languages such as Python, and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch).
  • Excellent analytical and problem-solving skills.
  • Strong communication and teamwork skills.
  • Attention to detail and ability to work independently.


Anticipated Schedule:

  • Monday and Wednesday from 11 am to 3 pm.


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