Master-Thesis Student (all genders) in our Biomarker Statistics Team

Looking to launch your career at the cutting edge of healthcare? Join Sanofi for a chance to develop with mentoring and guidance from inspirational leaders while helping to make an impact on the lives of countless people worldwide. As a Master-Thesis Student (all genders) in our Biomarker Statistics Team, you'll be leveraging AI techniques and internalizing AI algorithms for clinical trial outcome prediction.

About the job

We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people's lives. We're also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible.

We go 'all in' on digital and artificial intelligence (AI) approaches to accelerate research and development and bring medicine to patient at the right time.

Ready to join a motivated and highly skilled Biomarker Statistics Team?

Main responsibilities

During your master-thesis, you will be leveraging AI technics and internalizing AI algorithms for clinical trial outcome prediction. You will review several newly proposed AI-based approaches (e.g., HINT, SPOT, PlaNet and LLM-based approaches).

These approaches usually consider multi-modal data (e.g., drug molecule, target disease, eligibility criteria, safety, biological knowledge) and integrate all these data into a deep learning model to predict the success or failure of a given clinical trial before it starts, supporting some internal decision-making processes. Following the state-of-the-art review phase, you will internalize and test some of these algorithms on existing benchmarks and internal clinical trials. A rigorous evaluation on these approaches will be essential as it will serve as a basis to develop our own fit-for-purpose and end-to-end AI-based model for efficient clinical trial outcome prediction. Datasets and codes (Python) are released on GitHub.

About you

• You are a master's student in Statistics, (Bio)-Mathematics or equivalent, looking for a practice-oriented topic for your master thesis
  
• You have good knowledge and understanding of key statistical and machine learning/deep learning concepts and techniques
  
• You bring basic knowledge of pharmaceutical clinical development with you
  
• You have good knowledge of AI concept and techniques
  
• You are motivated to work in departmental computing environment, to do advanced statistical analyses using Python (e.g., TensorFlow, PyTorch, or Keras framework; Pandas, NumPy for data manipulation) and possibly other languages (R, R-Shiny)
  
• You have demonstrated interpersonal and communication skills and abiltiy to work in a cross-functional and global team setting
  
• You have very good communication in English, both oral and written
  

Why choose us?

• Bring the miracles of science to life alongside a supportive, future-focused team
  
• An international work environment, in which you can develop your talent and realize ideas and innovations within a competent team
  
• Discover endless opportunities to grow your talent and drive your career, whether it's through a promotion or lateral move, at home or internationally
  
• Benefit from our mobile office policy working up to 60% hybrid, depending on the area of assignment, within Germany
  
• Play an instrumental part in creating best practice
  
• Start your career at an attractive location in the center of Germany and experience our modern working environment
  

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