Jobs
1021 days ago
University Health Network -
A combination of engineered features and deep learning models will be used to extract and jointly analyze the imaging and genomic data. The first objective is to develop and evaluate novel computational imaging processing methods applied to multiple cancer types treated with chemotherapies, target therapies or immunotherapies. The second objective is to develop a cloud-based platform to facilitate the visualization and basic analysis of radiomics+genomics data in collaboration with the Software Engineers in the Haibe-Kains Laboratory (bhklab.ca).
This project (OCTANE 2.0) is funded by the Ontario Institute for Cancer Research and supported by Canexia Health. The candidate will be working in the Haibe-Kains Lab at the Princess Margaret Cancer Centre, University Health Network in collaboration with the Cancer Genomics Program and the Quantitative Imaging for Personalized Cancer Medicine, Techna Institute. A description of the project is available here.
1021 days ago
University of Iowa -
The Division of Biostatistics and Computational Biology offers multidisciplinary work environment and a highly collaborative culture. The research projects include developing computational pipelines/algorithms for microbiome omics data integration and analysis. We develop and apply bioinformatics approaches to forge quantitative links between genetic, taxonomic, and functional aspects of microbial diversity and activities. Other research opportunities include bioinformatics development for oral cancer omics data integration and analysis to discover cancer genetic susceptibility. We develop and apply computational systems biology approaches to investigate the landscapes of genetic content in human oral cancer to identify molecular biomarkers for oral squamous cell carcinoma by mining and integrating patterns discovered from combined large data of bulk RNA-seq, single-cell RNA-seq, and epigenomics data. Other projects include biological ontology mining and network analysis for genotype-phenotype associations and electronic health record data mining on integrated dental patient data and general hospital data to improve decision making and personalized treatment, etc. The successful applicant will be under the supervision of Dr. Erliang Zeng, Associate Professor whose research is primarily in bioinformatics and data science, and Dr. Xian Jin Xie, Division Director and the Association Dean for Research for the College of Dentistry, whose research is primarily in biostatistics and bioinformatics. Both Drs. Xie and Zeng are affiliated faculty in the Department of Biostatistics of College of Public Health and the multidisciplinary Informatics Program.
1053 days ago
Ontario Institute for Cancer Research -
Position: Postdoctoral Fellow in Computational Genomics
Site: MaRS Centre, Toronto
Department: Computational Biology
Reports To: Shraddha Pai
Salary: Commensurate with level of experience
Hours: 35 hours/week Status: Full-time, Temporary (1-year contract)
The Ontario Institute for Cancer Research (OICR) is seeking a dynamic, collaborative postdoctoral fellow to join a team developing computational algorithms for cancer drug target prioritization using genomics, biological networks, and systems medicine-based approaches.
The goal of the project is to create an algorithm to prioritize lead molecules for drug targeting by integrating prior ‘omic and non-‘omic knowledge to maximize functional relevance and minimize off-target effects. The algorithm will use network-based approaches, and will incorporate genomic prior knowledge such as tissue-specific transcriptomic and proteomic profiles, known oncogenic mutations, and target druggability, as well as non-‘omic sources such as reports of adverse drug reactions. The successful candidate will lead method development, benchmarking for method optimization, and manuscript writing of results. Prioritized molecules will be experimentally verified by members of the team from OICR’s Drug Discovery group.
The Pai Lab at the Ontario Institute for Cancer Research develops computational methods for precision medicine, with a focus on network and systems medicine. The project is a collaboration between the Ontario Institute for Cancer Research’s Adaptive Oncology and Drug Discovery teams, which includes the labs of Rima Al-Awar, Richard Marcellus, Lincoln Stein and Shraddha Pai. While this posting is for a one year initial contract, a contract extension for a second year is a strong possibility.
The successful candidate will gain the experience of working in an interdisciplinary team of computational biologists and pharmacologists, and be exposed to the process of drug discovery technology development. The candidate will be part of the rich scientific environment of the OICR, with opportunities for development of technical, leadership, and entrepreneurial skills. The candidate will also have the opportunity to learn about the space for biomedical technology development for commercialization.
The MaRS Centre has a mandatory COVID-19 vaccination policy in place that requires proof of full COVID-19 vaccination or proof of a medical exemption issued pursuant to the Government of Ontario guidelines. Accordingly, as a condition of employment, new employees who are required to work on-site are required to be fully vaccinated for COVID-19 subject to the duty to accommodate on the basis of protected grounds pursuant to the Ontario Human Rights Code.
Fully vaccinated is defined as having received all of the required doses of a Health Canada approved vaccine and having received the final dose at least 14 days before your employment start date.
As described above, the requirement to be fully vaccinated is subject to the Ontario Human Rights Code. If the candidate is unable to receive the COVID-19 vaccine for a reason protected by the Code, requests for accommodation from the vaccine policy will be assessed on a case-by-case basis.
To learn more about working at OICR, visit our career page.
1053 days ago
University of British Columbia -
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. Organizational Status: The successful candidate will report to the Principal Investigator (Director of AI Research at OVCARE, Dr. Ali Bashashati).
1053 days ago
University of Arizona -
An NIH R01-supported postdoctoral fellow position in bioinformatics is available within the Kruer laboratory of the Phoenix Children’s Hospital Research Institute and University of Arizona College of Medicine – Phoenix. Work in the lab focuses on neurodevelopmental and neurodegenerative disorders of childhood, spanning both common and rare diseases. Successful candidates will have strong programming and analytical skills. The fellow will take ownership of projects integrating genomic (WES and WGS) and transcriptomic datasets across eukaryotic systems working collaboratively with bench scientists (molecular & cellular biologists, geneticists, neuroscientists) and physicians within the lab to characterize fundamental disease mechanisms. Opportunities in phenomics, metabolomics, algorithm development, and single cell analysis exist. Early career scientists will receive mentoring in proposal development, grantwriting, peer review and scientific communication to complement their professional development and prepare for positions in either academia or industry. The successful applicant will have opportunities to work both independently and as part of large collaborative teams across major research networks and to publish high-impact manuscripts.