Now Hiring: Machine Learning Intern

“If you are interested in applying computational biology to real-world applications that could potentially lead to publishable research work, this is the right opportunity for you. Be a part of the team of research and machine learning scientists and get mentored by some of the best minds in AI.”

- Shazan Jabbar - Lead Machine Learning Scientist and Mara Cairo, Product Owner - Apprenticeships

About Amii

One of Canada’s three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world’s top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

The Project

In this project we propose to start by building on two current approaches for predicting relative biomolecule abundance that have shown promise in other species and for which NRC-generated data is available or planned. The approaches that are identified to investigate further are: 1) Ortholog contrast models and 2) Massively parallel reporter-based models. Both of these approaches take advantage of the recent advancement in deep learning models. NRC data will be limited to sequence information from plant protein crops, specifically canola and pulses (peas, lentils), with priority given to seed-related traits. As a first step, the above existing approaches will be validated by reproducing the published results. Then those calibrated models will be applied to NRC data. Following this demonstration, the focus will shift to ways to improve the model performance. Possible avenues to explore here would include feature engineering, data expansion, transfer-learning, and addressing data-quality issues.

The outcome of this project will be a first generation of predictive models of molecular phenotype (aka endophenotype) abundance. These models are expected to have wide ranging utility for crop improvement. By providing a means to elevate trait associations and modelling to a functional level (i.e. transcript, protein or gene/functional dosage), these types of models are expected to drive a paradigm shift in breeding and trait development.

The project will be executed across a two-year time period, and Amii will onboard a number of consecutive interns over the course of the project. The interns will work under the supervision of an Amii Lead Scientist for the duration of their internship. Internships start at 4 months with the possibility of extension of up to 12 months.

Required Skills / Expertise

We’re looking for a talented and enthusiastic Intern with a strong knowledge of computational biology and machine learning.

Key Responsibilities

• Build, train, and evaluate ML models
• Undertake applied research on ML techniques to address the limitations in existing models

Requirements

• At least one year into a CS / ML graduate program, MSc. or PhD.
• Research and/or applied project experience in computational biology and related Deep Learning Technologies (e. g. Convolutional Neural Networks (CNN), Sequence models)
• Proficient in Python programming language and related libraries and toolkits (e.g. scikit learn, Pandas, Jupyter notebooks, Keras, Tensorflow, transformers)

Assets

• Experience working with data engineering workflows and databases
• Publication record in peer-reviewed academic conferences or relevant journals in machine intelligence
• Knowledge and experience in designing experimental frameworks for large datasets

Non-technical Requirements

• Interdisciplinary team player enthusiastic about working together to achieve excellence
• Capable of critical and independent thought
• Able to communicate technical concepts clearly and advise on the application of machine intelligence
• Intellectual curiosity and the desire to learn new things, techniques, and technologies

What you'll love about us

• A professional yet casual work environment that encourages the growth and development of your skills.
• A chance to learn from amazing teammates who support one another to succeed.
• Competitive compensation, including paid time off and flexible health benefits.
• A modern office located in downtown Edmonton, Alberta.

Why You Should Apply

Besides gaining industry experience, additional perks include:

• Get paid for your work
• Work under the mentorship of an Amii Lead Scientist for the duration of the project
• Participate in professional development activities
• Gain access to the Amii community and events
• Build your professional network

How to Apply

If this sounds like the opportunity you've been waiting for, then please don’t wait to apply! Please send your resume and cover letter indicating why you think you'd be a fit for Amii by December 1 through the Indeed listing.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is proud to be an equal opportunity employer. We are committed to creating a diverse, inclusive and excellent workforce.