Computational Chemistry & AI Intern (Stage)

About the Role:

We are seeking a highly motivated and curious Computational Chemistry & AI Intern to join our team. This stage offers a unique opportunity to gain practical, hands-on experience in applying cutting-edge AI methods to accelerate early drug discovery. The successful candidate will work closely with senior scientists to assist in evaluating drug-like molecules potential. This internship is ideal for a student finishing a Master’s degree who is passionate about the intersection of AI, computational science, and chemistry.

Responsibilities:

• Support the development and application of AI/ML models for molecular design, focusing on key properties like potential activity or toxicity.
• Conduct literature reviews on emerging AI/ML methods, technologies, and best practices in computational chemistry.
• Assist in data preparation and model training using high-performance computing resources.
• Collaborate with the multidisciplinary research team by analyzing results and presenting findings.
• Actively participate in team meetings and learn about the strategic direction of research projects.

Qualifications:

• Currently pursuing or recently completed a Master's degree in a relevant field such as: Computer Science, Chemistry, Mathematics, Statistics, Physics, or a related computational discipline.
• Coursework or project experience in AI/Machine Learning and/or computational chemistry.
• Familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow).
• Basic knowledge of Linux/Unix environments and cloud or high-performance computing (HPC) concepts is a plus.
• High motivation to learn and an enthusiastic, proactive approach to problem-solving.
• Ability to work in a collaborative and international setting.
• Good communication skills in spoken and written English.

Required Skills:

• Currently pursuing or recently completed a Master's degree in a relevant field such as: Computer Science, Chemistry, Mathematics, Statistics, Physics, or a related computational discipline.
• Coursework or project experience in AI/Machine Learning and/or computational chemistry.
• Familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow).
• Basic knowledge of Linux/Unix environments and cloud or high-performance computing (HPC) concepts is a plus.
• High motivation to learn and an enthusiastic, proactive approach to problem-solving.
• Ability to work in a collaborative and international setting.
• Good communication skills in spoken and written English.

Preferred Skills:

• Basic understanding of Graph Neural Networks (GNNs) or Transformer architectures.
• Familiarity with the concepts behind deep generative models (e.g., VAEs, GANs, Flows).
• Any project experience related to drug discovery or the prediction of ADMET properties.