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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.

Documentation:

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

Requirements

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:

Job Contact: