Jobs

Date: September 23, 2024

Postdoc/PhD positions in saRNA for Vaccine Development

We are seeking applications for multiple Senior Researcher positions, available immediately for exceptionally motivated Postdoctoral Fellows or PhD students. These positions offer a unique opportunity to contribute to a pioneering project applying artificial intelligence and machine learning to the development of RNA vaccines against emerging viral threats such as Influenza, Lassa, and Orthopox viruses.

Project Overview: This ambitious project utilises self-amplifying RNA (saRNA) technology, which offers the potential for more potent immune responses at lower doses compared to traditional mRNA vaccines. Our approach focuses on the use of structural RNA bioinformatics to design vaccine candidates and predict the effects of viral mutations, enhancing our ability to respond rapidly to evolving pandemic threats.

A post-doctoral fellowships (PDF) position in the field of machine learning/computational biology is available in the School of Biomedical Engineering and Department of Pathology and Laboratory Medicine at the University of British Columbia/Vancouver General Hospital. The incumbents will join an interdisciplinary team working to establish a program on machine learning applications in pathology and genomics. Candidates are expected to have extensive experience in one or more of the following areas: diverse areas of machine learning and statistics especially deep neural networks, statistics, and image processing.

The candidate will play an important role in the project team, including authoring grants, conducting large-scale international projects, managing collaborations, disseminating research findings, and assisting in managing junior lab members.

The successful candidate will report to the Principal Investigator (Director of AI Research at OVCARE, Dr. Ali Bashashati).

We invite applications for a postdoctoral position in the CSG lab (http://csg.lab.mcgill.ca/) at McGill University. The successful candidate will join an interdisciplinary team of computational and experimental biologists working at the intersection of machine learning, statistical inference, and genomics to understand the genetic and molecular basis of gene regulation, characterize the role of gene regulatory factors in determining cell identity and function, and uncover the gene regulatory basis of human diseases.

Research areas that we are excited about include, but are not limited to, development of new statistical and machine learning methods for analysis of high-dimensional multi-modal omics data, machine learning-based sequence-to-activity models, and AI models for omics-based diagnosis and prognosis of diseases.

The Gastrointestinal (GI) Oncology Translational Lab at Weill Cornell Medicine in New York City is seeking a highly skilled computational biologist with a strong analytical background, driven to tackle the mysteries of biology with high-throughput data. We are looking for a bright and motivated person to join our research program to study tumor microenvironments, unique molecular disease subtypes, and their relation to resistance and sensitivity to cytotoxic therapy and immunotherapies. The Translational Lab (PI Manish A. Shah, MD) in the GI Oncology program at Weill Cornell is a multidisciplinary group focused on novel drug and immunotherapy development across GI malignancies (https://shahlab.weill.cornell.edu/).  Drivers of resistance including disease subtypes, the tumor microenvironment, and host factors are explored in preclinical models and from blood and tissue samples across an array of patients treated on clinical trials.

This position combines the best aspects of industry and academia; it is ideal for PhD graduates looking to work in a thriving and stimulating research environment on cutting-edge medical and clinical research projects, directly impacting multiple research efforts. The focus of our work is to understand the data at hand and how it relates to the initial research question. If you enjoy detail-oriented data exploration, hypothesis testing, writing robust code, and contributing to a wide range of research projects, then this job is for you!