Position Overview
We are seeking a deep learning scientist to develop AI models for predicting and optimizing enzymes and metabolic pathways in microbial systems. The role involves metabolic network modeling, data analysis, and collaboration with multidisciplinary teams to drive innovations in industrial biotechnology. Candidates should have strong deep learning expertise, proficiency in Python or similar languages, and excellent communication skills. Knowledge of biological systems, metabolic flux analysis, or protein modeling is a plus. This is a dynamic start-up environment requiring adaptability, initiative, and scientific rigor.
Key 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.
- Communicate results and insights to multidisciplinary teams, including presentations and written reports.
Required Qualifications
- Ph.D. Computer Science, or any similar disciplines such as physics, mathematics, with a strong focus on deep learning.
- 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.