Computational Research Scientist Deep Learning

We are seeking a passionate and highly skilled Computational Research Scientist specializing in deep learning to join our R&D team. This role will focus on developing and applying advanced AI and machine learning methods to solve biological problems, with an emphasis on enzyme optimization, metabolic engineering, and bio-process innovation. The successful candidate will collaborate closely with biologists, engineers, and data scientists to accelerate the design and production of sustainable bio-alternatives.

• Design, develop, and deploy deep learning models for predicting and optimizing enzymes, proteins, and metabolic pathways in microbial and cellular systems.
  

• Conduct computational modeling and simulations of metabolic networks to identify critical control points and engineering targets.
  

• Build robust data pipelines to integrate diverse biological datasets and enable scalable model training and evaluation.
  

• Present technical findings clearly to interdisciplinary teams through reports, presentations, and collaborative discussions.
  

• Stay current with advances in AI, synthetic biology, and computational methods to drive innovation at ThinkBio.Ai.
  

• Ph.D. in Computer Science, Bioinformatics, Computational Biology, or a related field with a focus on deep learning applications.
  

• Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or similar.
  

• Proficiency in programming languages including Python (preferred), R, or MATLAB.
  

• Strong written and verbal communication skills.
  

• Proven ability to work independently and collaboratively in a dynamic research environment.
  

• Knowledge of metabolic engineering, synthetic biology, or systems biology concepts.
  

• Familiarity with metabolic flux analysis and constraint-based modeling techniques (eg, Flux Balance Analysis, COBRA Toolbox).
  

• Experience with protein structure prediction and modeling.
  

• Background in industrial biotechnology or experience working in start-up environments.
  

• Exceptionally organized with the ability to manage multiple projects and priorities simultaneously.
  

• Quick learner with a proactive, inquisitive mindset.
  

• Adaptable and comfortable with evolving roles and responsibilities typical in start-ups.
  

• Strong collaborator with excellent interpersonal and communication skills.
  

• Commitment to high standards of scientific integrity and professional ethics.