We are looking for a postdoctoral fellow to lead a project on precision cancer medicine. The project is focused on developing deep learning models for prediction of drug response in cancer patients and identifying novel therapeutic targets. It involves utilizing large multi-omics datasets corresponding to preclinical and clinical samples (cell lines/organoids/xenografts/patients) to develop an accurate preclinical-to-clinical drug response prediction model. The predictions of the model will then be tested experimentally at Mayo Clinic for validation. The project is a close collaboration between Dr. A. Emad (McGill University and Mila, Canada) and Dr. Cairns (Mayo Clinic, USA).
– Develop and implement novel deep learning models for drug response prediction
– Analyze publicly available and in-house datasets containing genomic, transcriptomic, proteomic, epigenomic and clinical data
– Collaborate with wet-lab researchers and machine learning experts on the project
– Write scholarly articles and present the results of the project in scientific conferences
The ideal candidate will have the following qualifications:
1. A PhD degree in a related field (computer science, machine learning, bioinformatics,engineering, etc.) received in the last 3 years
2. Strong background in machine learning and particularly deep learning
3. Related background in ‘omics’ and computational biology is considered an advantage
4. Strong programming skills in python
5. At least two first-authored English papers (or three if co-first authors) with submitted,
accepted or published status in journals
6. Good spoken and written communication skills in English.
How to Apply:
Interested applicants should submit CV, a letter of interest, a one-page summary of the most relevant publication, and contact information for three references to Amin Emad (firstname.lastname@example.org) with subject line “postdoctoral application”.The position remains open until filled.