Computational Research Scientist Deep Learning

Role Overview: You will be responsible for developing AI models for predicting and optimizing enzymes and metabolic pathways in microbial systems. This role involves metabolic network modeling, data analysis, and collaboration with multidisciplinary teams to drive innovations in industrial biotechnology. Your strong expertise in deep learning, proficiency in Python or similar languages, and excellent communication skills will be essential. Knowledge of biological systems, metabolic flux analysis, or protein modeling will be advantageous. Adaptability, initiative, and scientific rigor are crucial in this dynamic start-up environment. 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 through presentations and written reports. Qualification Required: - Ph.D. in Computer Science, or 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. Desirable Additional Qualifications: - Familiarity with biological systems. - 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. Note: No additional details about the company were provided in the job description. Role Overview: You will be responsible for developing AI models for predicting and optimizing enzymes and metabolic pathways in microbial systems. This role involves metabolic network modeling, data analysis, and collaboration with multidisciplinary teams to drive innovations in industrial biotechnology. Your strong expertise in deep learning, proficiency in Python or similar languages, and excellent communication skills will be essential. Knowledge of biological systems, metabolic flux analysis, or protein modeling will be advantageous. Adaptability, initiative, and scientific rigor are crucial in this dynamic start-up environment. 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 through presentations and written reports. Qualification Required: - Ph.D. in Computer Science, or 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. Desirable Additional Qualifications: - Familiarity with biological systems. - 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. Note: No additional details about the company were provided in the job description.