(Senior) Scientist, AI Researcher - AIDD

Key Skills

3D CAD, Aartificial intelligence, AIOps, ChatGPT, Deep Learning, Effective communication skills, Large Language Models - LLMs, Machine learning techniques, PyTorch, TensorFlow

Job Description

Responsibilities:

• You will be a key individual contribute to our AI strategy and the AI pillar of the AIDD team to increase the success rate of drug portfolio projects and the productivity of R&D.
• You will identify, develop, and implement appropriate AI solutions to generate scientific insights (e.g. target identification, molecule design & prediction), automate processes (e.g. lab automation), and complement traditional computational approaches by close collaboration within the AIDD team (e.g. CADD, Bioinformatics, Digital, etc.).
• You will explore and apply generative AI approaches including large language models (LLMs, e.g. ChatGPT, LLaMA, etc.) and their applications (e.g. BioGPT, ChemCrow, AutoGPT, etc.) to aid drug R&D.
• You will communicate with data scientists, AI researchers and informatics experts across Roche organization (e.g. pRED, Genentech, Roche Informatics, etc.) to exchange learnings and collaborate on projects.
• You will have the opportunities to lead the AI intuitive or projects across CICoR or Roche global sites.

Requirements:

• Ph.D. or M.S. degree in machine learning, computer science, mathematics, physics, biology, chemistry or a relevant discipline.
• 3+ years of industry experience, preferred in pharmaceutical (MNC/biotech), internet, or AI startup companies.
• Passion for applying AI in different fields of drug R&D: cheminformatics, bioinformatics, biomedical, lab automation, as well as learning relevant scientific domain knowledge.
• A proven track record of successfully developing ML/DL models to solve the scientific problems (preferred in pharma industry) and leading the projects with the teams to implement impactful AI solutions.
• Strong expertise and hands-on experience in applying state-of-the-art deep learning model development, including graph neural networks (GNNs), transformers, generative networks (e.g. LLMs, diffusion models), and convolutional neural networks (CNNs), etc.
• Excellent analytical and mathematical capabilities, being able to identify key questions and come up with innovative AI solutions.
• Excellent in programing language especially python, as well as other commonly used machine learning and deep learning frameworks, such as Scikit-learn, PyTorch, TensorFlow.
• Experience in training and optimizing ML/DL models, including hyper-parameter tuning, regularization techniques, and model evaluation methods.
• Experience in multi-modal deep learning frameworks and solutions is a plus.
• Experience in AI model operationalization (AIOps), container orchestration platforms (e.g. Kubernetes) and cloud-native application development is a plus.
• Good communication skills in both English and Mandarin.
• Collaborative team player.