Postdoctoral Researcher - Toronto, Canada - University Health Network

University Health Network

Verified Company

Toronto, Canada

2 weeks ago

Posted by:

Sophia Lee

beBee Recruiter

Description

Job Tittle:
Postdoctoral Researcher

Job Posting: 928900

Union:
Non-Union

Site:
Princess Margaret Cancer Centre

Department:
Princess Margaret Research Institute

Reports to:
Principal Investigator

Hours:37.5 hours per week

Salary:
$51,750 minimum, annually
:To commensurate with experience and consistent with UHN compensation policy

Status:
Temporary Full-time (2 years)

Posted Date:
February 16, 2024

Closing Date:

March 17, 2024**The University Health Network, where "above all else the needs of patients come first", encompasses Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute and the Michener Institute of Education.

The breadth of research, the complexity of the cases treated, and the magnitude of its educational enterprise has made UHN a national and international resource for patient care, research and education.

With a long tradition of ground breaking firsts and a purpose of "Transforming lives and communities through excellence in care, discovery and learning", the University Health Network (UHN), Canada's largest research teaching hospital, brings together over 16,000 employees, more than 1,200 physicians, 8,000+ students, and many volunteers.

UHN is a caring, creative place where amazing people are amazing the world.

Position Summary

We seek a postdoctoral fellow to develop innovative machine learning (ML) and deep learning (DL) methods to predict drug-like small molecules from large chemical screens based on the DNA Encoded Library (DEL) and Affinity Selection Mass Spectrometry (ASMS) technologies.

Duties

Develop and implement novel ML/DL algorithms to predict druglike small molecules from largescale chemical screening datasets.
Utilize computational approaches to analyze complex drug screening data and extract meaningful insights.
Collaborate with computational biologists and software developers to build, validate predictions and deploy models on the AIRCHECK
Contribute to the design and execution of experiments to validate target predictions.
Stay abreast of the latest advancements in machine learning, AI, and chemical biology research.

Required Qualifications

Doctorate in computational chemistry, computer science, engineering, applied physics or equivalent.
Strong background in AI, deep learning, and machine learning.
Published/submitted papers in Scientific Journal or Conference Proceedings.
Experience with analysis of highthroughput drug screening data, such as DNA-Encoded Library (DEL) and/or Affinity Selection Mass Spectrometry (ASMS).
Strong data engineering skills.
Strong expertise in programming and machine learning (eg, PyTorch, VertexAI, Flask, TensorFlow).
Excellent communication skills and ability to work effectively in a collaborative research environment.

Preferred qualifications

Prior experience in computational chemistry or drug discovery research.
Knowledge of cheminformatics, structural bioinformatics, or systems biology.
Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
Experience with highperformance computing and cloud computing platforms like Google Cloud Platform.

Benefits

Competitive salary commensurate with experience.
Comprehensive benefits package including health insurance, retirement plans, and paid time off.
Opportunities for professional development and career advancement.
Access to cuttingedge computational resources and stateoftheart laboratory facilities.
Collaborative and inclusive work environment that fosters creativity and innovation.

How to apply

Deadline
Applications must be submitted before
March 17, 2024.

Team

The Haibe-Kains Lab
The Schapira Lab
The Arrowsmith Lab

Founded in 2003, the Structural Genomics Consortium (SGC) is a pre-competitive public-private partnership in the areas of structural and chemical biology dedicated to open science and drug discovery.

SGC collaborates with researchers worldwide to support breakthrough research in protein-focused open science tools, knowledge, and reagents.

As part of their ongoing projects, they employ advanced methodologies such as high-throughput protein production and assays, and structure-guided development of chemical probes.

SGC is the largest contributor of human protein structures to the Protein Data Bank, which enabled Google DeepMind's breakthrough in protein structure prediction.

SGC is now embarking on a mission to be the largest contributor of chemical screening data to enable an AI-driven breakthrough in computational drug design, with AIRCHECK as the core repository.

Why join UHN?

In addition to working alongside some of the most talented and inspiring healthcare professionals in the world, UHN offers a wide range of benefits, programs and perks.

It is the comprehensiveness of these offerings that makes it a differentiating factor, allowi