Postdoctoral Fellowship in Machine Learning for Imaging and Understanding Flow in Microfluidic Bioprinting Systems

We are seeking a Postdoctoral Researcher to work on a collaborative project between the Walus Lab at UBC Vancouver and Aspect Biosystems Ltd. This role aims to advance Machine Learning and Machine Vision applications in 3D Bioprinting, specifically focusing on Aspect Biosystems unique microfluidic platform.

The PDF researcher will develop innovative machine vision and machine learning approaches to mapping and analyzing flow of biomaterials and cells in the microfluidic 3D bioprinting systems being developed by Aspect Biosystems. Candidates are expected to have proven experience developing state-of-the-art applications of machine learning and machine vision and preferably an understanding of ML/MV applications to liquid flow phenomena.

What you will be working on:

  • Research and develop state-of-the-art computer vision, data science, and deep learning technologies.
  • Work on high-impact real-world problems and datasets, including image and video analysis, motion tracking, optical flow estimation, data mining, knowledge discovery, structure prediction, data generation and translation, supervised, self-supervised, and unsupervised learning, active learning, and model uncertainty. 
  • Contribute to end-to-end ML software development from problem formulation and data curation to model design, optimization, evaluation, and deployment.

Appropriate Background:

  • Education: PhD in applications of machine learning and machine vision preferably direct applications to imaging and studying flow phenomena.
  • Development Experience: Hands-on experience in rapid prototyping with machine learning and deep learning libraries. Preferably also with familiarity of cloud computing, AWS, Google Cloud, Azure, etc.
  • Software Experience: Experience in planning and executing reliable and test-driven code. Understanding Git and familiarity with code, data, and ML experiments version-control practices.
  • Technical Skills Set: Machine learning, data analysis, database, and scientific computing packages, e.g., PyTorch, Tensorflow, Scipy, Scikit-learn, Pandas, SQL. Familiarity with CUDA programming.
  • Problem Solver: Demonstrated ability to identify innovative working solutions to problems with challenging constraints.
  • Effective Communicator: You have superior written and verbal communication skills. You are an active listener who can communicate to different audiences in diverse situations.
  • Detail Oriented: You have outstanding attention to detail, and experimental and process rigor. You take pride in your work and strive for excellence in the work you do.
  • Go-Getter: You work with a sense of urgency, are results-driven and thrive in a fast-paced, interdisciplinary, and entrepreneurial environment. You are willing to roll up your sleeves and do what it takes to get the job done.
 
Reference Number

Please mention reference number GPS-56791 in all your correspondence about this Postdoctoral Fellow position.

 
 
 
 
 

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