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Job Requirements of Computational Scientist:
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Employment Type:
Contractor
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Location:
Mississauga, Ontario (Onsite)
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Computational Scientist
Job Title: Computational Scientist
Location: Remote (Canada-based)
Duration: 12+ Months
Work Authorization: Must reside in Canada with valid legal work authorization
Role Overview:
A leading biopharma is seeking a highly motivated Computational Scientist to join the Perturbation Pillar within the Foundation Data for Foundation Models (FDFM) Initiative under gRED (Genentech Research and Early Development). This role focuses on analyzing high-content perturbation screening data (e.g., Perturb-seq, CROP-seq) to drive early insights for drug and target discovery, especially in oncology. The successful candidate will work in a collaborative, interdisciplinary environment contributing to foundational data used in training large-scale perturbation models.
Key Responsibilities:
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Analyze large-scale, sequencing-based perturbation datasets (e.g., Perturb-seq, CROP-seq).
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Collaborate with biologists, chemists, data scientists, and cross-functional partners.
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Partner with gRED Computational Sciences (gCS) and therapeutic area leads to generate insights for oncology pipelines.
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Contribute to shared computational pipelines and infrastructure across the organization.
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Support the development of lab-in-the-loop capabilities through foundational model training.
Qualifications & Skills:
Education:
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PhD in a quantitative field (e.g., Computational Biology, Bioinformatics, Computer Science, Statistics, Mathematics) or in physical/life sciences with a strong computational focus.
Required Experience:
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Demonstrated experience analyzing Perturb-seq or CROP-seq datasets.
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Proven interest in biology and chemistry problems related to drug discovery.
Technical Proficiency:
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Strong programming skills in Python.
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Solid foundation in statistics, data analysis, and probabilistic modeling.
Soft Skills:
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Excellent communication and teamwork abilities.
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Strong analytical and problem-solving mindset.
Research Background:
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Strong publication record in relevant fields.
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Demonstrated contributions to scientific or open-source communities (e.g., GitHub, public presentations).
Preferred Qualifications:
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Experience with multimodal data integration, especially integrating sequencing data with clinical or other measurement modalities.