Machine Learning Scientist - Computational Biology (Multiple Levels)
Deep Genomics
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See open jobs at Deep Genomics.See open jobs similar to "Machine Learning Scientist - Computational Biology (Multiple Levels)" Work In Tech.Key Responsibilities
- Develop and implement advanced machine learning models for RNA biology, systems biology, and structural biology to solve frontier challenges in drug discovery.
- Collaborate with cross-functional teams (e.g., ML engineering, target discovery, and experimental biology) to drive research projects that identify novel drug targets and preclinical candidates.
- Design and execute computational and experimental studies to validate and improve model predictions.
- Stay informed about the latest advancements in machine learning and computational biology, and apply them to real-world challenges.
- Share research findings through presentations, publications, and technical discussions.
Basic Qualifications
- PhD in Machine Learning, Computational Biology, Bioinformatics, Computer Science, or a related technical field (MSc with significant experience also considered).
- Extensive experience in designing, training, debugging, and evaluating machine learning models using frameworks like PyTorch, TensorFlow, or JAX.
- Strong foundation in mathematics and statistics, including linear algebra, probability, and optimization.
- Excellent scientific writing and communication skills.
Preferred Qualifications
- Experience in computational biology, genomics, or drug discovery.
- Familiarity with RNA biology, structural biology, or systems biology.
- Proven track record of publishing in top-tier conferences or journals.
- Experience developing machine learning models for production, particularly in drug design.
- Proficiency with cloud computing platforms (e.g., AWS, GCP) or distributed computing frameworks.
What we offer
- A collaborative and innovative environment at the frontier of computational biology, machine learning, and drug discovery.
- Highly competitive compensation, including meaningful stock ownership.
- Comprehensive benefits - including health, vision, and dental coverage for employees and families, employee and family assistance program.
- Flexible work environment - including flexible hours, extended long weekends, holiday shutdown, unlimited personal days.
- Maternity and parental leave top-up coverage, as well as new parent paid time off.
- Focus on learning and growth for all employees - learning and development budget & lunch and learns.
- Facilities located in the heart of Toronto - the epicenter of machine learning and AI research and development, and in Kendall Square, Cambridge, Mass. - a global center of biotechnology and life sciences.