Computational Research Scientist, Deep Learning

Job Description

Computational Research Scientist, Deep Learning

Responsibilities:

• Develop and implement deep learning models to predict and optimize enzymes and metabolic pathways in microbial systems.
• Conduct simulations and modeling of metabolic networks to identify key regulatory nodes and potential engineering targets.
• Perform protein variant designs with established protocols to support in-house projects.
• Collaborate with experimental biologists to design and interpret experiments that validate computational predictions.
• Communicate results and insights to multidisciplinary teams, including presentations and written reports.

Required qualifications:

• Ph.D. in Bioengineering, Biochemistry, Biostatistics, Chemical Engineering, Computer Science, or similar discipline, with a strong focus on deep learning and/or cell engineering
• Proven experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries.
• Proficiency in programming languages such as Python, R, or MATLAB
• Excellent communication skills, both written and verbal

Preferred qualifications:

• Familiarity with metabolic engineering and synthetic biology principles
• Knowledge of metabolic flux analysis and constraint-based modeling (e.g., FBA, COBRA toolbox)
• Knowledge of protein structural modeling and prediction
• Experience in industrial biotechnology or a related industry

Preferred Working Style:

• Must be very well-organized and be able to handle multiple projects simultaneously.
• Must be a quick learner who is self-motivated and able to ask questions and seek clarity.
• Must be flexible with day-to-day duties and able to thrive in a start-up environment.
• Must be an excellent team member with strong communication skills and a desire to work collaboratively.
• Must hold themselves to the highest professional, scientific and ethical standards.