The Computational Biology & Gene Regulation group led by Anthony Mathelier at the NCMM, a part of the Nordic EMBL Partnership for Molecular Medicine, is seeking a highly motivated Researcher or Postdoctoral Fellow for a two-year position, starting as soon as possible in 2024. The selected candidate will play a pivotal role in a collaborative project spanning internationally renowned groups, namely those of Drs. Anshul Kundaje at Stanford University, USA, Wyeth Wasserman at the University of British Columbia, Canada, and Anthony Mathelier, NCMM, Norway. The position will be based in Norway. More information about the group can be found at https://mathelierlab.com/.

Join us to not only advance your career but also contribute to meaningful scientific discoveries and resources in the world of computational biology and gene regulation.

Position Description

The selected candidate will contribute to a cutting-edge project aimed at enhancing and expanding computational resources to decipher transcription factor (TF) – DNA interactions. The focus will be on the enhancement of the JASPAR (https://jaspar.elixir.no) and UniBind (https://unibind.uio.no) databases, which ELIXIR Norway recognizes as a Norwegian bioinformatics service. Specifically, the candidate will utilize advanced deep learning techniques to provide refined models and data crucial for the analysis of disease mutations affecting gene expression.

The candidate can refer to the following publications, which can be discussed during the interview: https://doi.org/10.1093/nar/gkad1059, https://doi.org/10.1186/s12864-021-07760-6, https://doi.org/10.1038/s41588-021-00782-6.

Postdoctoral Positions in Etienne Caron Lab at Department of Immunobiology, Yale School of Medicine. The Caron Lab seeks postdoctoral applicants with a passion for innovation in mass spectrometry-based immunopeptidomics research. The overarching goal of the Caron Lab is to develop and apply mass spectrometry-based methods and systems immunology approaches to understand the generation, composition and dynamics of both the self and nonself immunopeptidome, as well as its interaction with T cells, with the ultimate goal of innovating treatments and preventive strategies for a broad range of immune-related diseases.

Opportunities and Benefits. Postdocs will have the opportunity to gain expertise in mass spectrometry, systems immunology, spatial immunopeptidomics, T-cell epitope discovery, immunology, and vaccine design. The selected candidates will also have the opportunity to become active players within several Yale Centers, including the Yale Center for Immuno-Oncology (YCIO), Center for Infection and Immunity (CII), and Center for Systems and Engineering and Immunology (CSEI). Strong support will be given to purse independent directions. Postdoc compensation and benefits will be according to Yale policies. More information about salaries and other resources can be found at https://postdocs.yale.edu/.

Lab website: https://phulab.org/

The Hu lab in the Department of Biochemistry and Department of Computer Science at Western University, Canada is recruiting two postdoctoral fellows in artificial intelligence for health data science/bioinformatics. Western University ranks within the top 10 research-intensive universities in Canada and top 114 in the world (QS World University Rankings 2024). Dr. Hu is a Canada Research Chair in Computational Approaches to Health Research and has excellent experience in mentoring trainees at different levels. Many of his trainees have received international and national awards, were accepted into top graduate schools (like Oxford, Cambridge, UCLA, CMU, Toronto, UBC, McGill), are employed in high-tech companies (like Google, Microsoft, Amazon), and landed tenure-track professor positions in Canada.

Professor Yue Li is hiring one Postdoc for the machine learning and AI research in healthcare. The position will be held at the School of Computer Science.

The broad adoption of electronic health records (EHR) systems has created rich digital healthcare data and opportunities for conducting transformative health informatics research. However, irregular patient visits, heterogeneous data modalities, restricted EHR data access, and data distribution shifts among hospitals hinder their full utility. Rapidly advancing machine learning (ML) research offer great promise including transformer-based deep generative models and federated learning framework.

In Li lab, we develop explainable AI (xAI) methods that adapt the state-of-the-art AI methods for real-world life science applications pertinent to human health. In a funded project, we proposed 3 aims:

Aim 1: Predicting patient health trajectories using AI. Through our collaboration with the co-PIs at the McGill University Health Centre (MUHC), we have access to irregular longitudinal patient records for over one million patients from Montreal metropolitan area. We will develop a foundational “HealthGPT” model with a focus on predicting future health trajectories of patients by learning the hidden clinical semantics from pretraining on the massive EHR data. We will adapt the recently developed time-series transformer architectures to effectively account for the unequally spaced time-series time in our EHR data.

Aim 2: Robust federated learning in healthcare sectors. Training large neural networks to learn clinical semantics requires big data. Through our extended network, we can gain secure access to patient data on-site beyond MUHC. By using federated learning (FL) framework, we can aggregate model parameters in a central server without sharing the patient data from each hospital. To build a robust FL model, we will tackle data distribution shifts or out-of-distribution (OOD) challenges among hospitals. We will use deep density estimators to model the distributions within health centres and train OOD-aware AI models that are tailored to each hospital in their prediction tasks while harnessing the information across hospitals.

Aim 3: building real-world deployable software healthcare system for federated learning. While many FL algorithms in healthcare were developed, very few have been deployed in the real-world healthcare systems. This aim addresses the software engineering problem in building secure, robust, and efficient network communications between hospitals to deploy state-of-the-art AI methods in the health systems using/adapting existing FL frameworks such as Flower (https://flower.dev/).

Name of the immediate Supervisor:           Yue Li

Work schedule:         Five working days (Monday through Friday)

Working hours:         40 hours per week, 9 a.m. to 5 p.m.

Work location:           Trottier building at McGill Downtown campus

Salary information:   50,000 / year + benefits

 Planned start and end dates of appointment (if applicable):

The position can start on September 1, 2023, and ends on September 1, 2024. The position can be extended by 1 year.

To apply:  Send your CV and cover letter to : yueli@cs.mcgill.ca

JOB TITLE: Post-Doctoral Fellow in Computational Cancer Biology

Job Posting #: 924521

Site: Princess Margaret Research Institute

Department: Princess Margaret Cancer Center Living Biobank (PMLB)

Reports to: Principal Investigator

Hours: 37.5

Salary: $60,000 – 75,000: To commensurate with experience and consistent with UHN compensation policy

Status: Temporary Full-time (1 Year; with possible extension)

Posted Date: September 16,2023

Closing Date: December 1, 2023

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

The PM Living Biobank is headed by Dr. Ming-Sound Tsao, who has over 30 years of experience in cancer pathology. He is the (co-)author of more than 600 peer-reviewed articles in top epigenomic, biology and clinical journals. For an exhaustive list of publications, go to Dr. Tsao’s Google Scholar Profile. Dr. Haibe-Kains has over 15 years of experience in computational analysis of genomic and transcriptomic data, in the context of translational research. He is the (co-)author of more than 200 peer-reviewed articles in top bioinformatics and clinical journals. For an exhaustive list of publications, go to Dr. Haibe-Kains’ Google Scholar Profile. Dr. Lupien has over 20 years of experience in computational analysis of genomic and transcriptomic data, in the context of translational research. He is the (co-)author of more than 130 peer-reviewed articles in top epigenomic, biology and clinical journals. For an exhaustive list of publications, go to Dr. Lupien’s Google Scholar Profile.

The candidate will work in a large multidisciplinary team of 8 laboratories from the Princess Margaret Cancer Centre as part of as part of Terry Fox New Frontiers Research Project:

• The PM Living Biobank: https://pmlivingbiobank.uhnresearch.ca/
• The Haibe-Kains Lab: https://www.bhklab.ca/
• The Lupien Lab: https://www.pmgenomics.ca/lupienlab/