Auf einen Blick
- Aufgaben: Leverage AI techniques for clinical trial outcome prediction during your master thesis.
- Arbeitgeber: Join Sanofi, a global healthcare innovator dedicated to improving lives through science.
- Mitarbeitervorteile: Enjoy a hybrid work policy, international opportunities, and a supportive team environment.
- Warum dieser Job: Make a real impact in healthcare while developing your skills in a cutting-edge field.
- Gewünschte Qualifikationen: Master's student in Statistics or (Bio)-Mathematics with knowledge of AI and statistical techniques.
- Andere Informationen: Work with advanced tools like Python, TensorFlow, and collaborate in a global team.
Das voraussichtliche Gehalt liegt zwischen 36000 - 60000 € pro Jahr.
Master-Thesis Student (all genders) in our Biomarker Statistics Team
Apply locations: Frankfurt am Main
Time type: Full time
Posted on: Posted 3 Days Ago
Time left to apply: End Date: March 31, 2025 (30+ days left to apply)
Job requisition id: R2777004
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.
Ready to join a motivated and highly skilled Biomarker Statistics Team?
Main responsibilities
During your master-thesis, you will be leveraging AI techniques 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 concepts and techniques.
- You are motivated to work in a 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 ability 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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Pursue progress , discover extraordinary
Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.
At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, ability or gender identity.
Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!
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Master-Thesis Student (all genders) in our Biomarker Statistics Team Arbeitgeber: Sanofi

Kontaktperson:
Sanofi HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Master-Thesis Student (all genders) in our Biomarker Statistics Team
✨Tip Number 1
Familiarize yourself with the latest AI techniques and algorithms relevant to clinical trial outcome prediction. This knowledge will not only help you during the interview but also demonstrate your genuine interest in the role.
✨Tip Number 2
Engage with current research and publications in biomarker statistics and AI applications in healthcare. Being able to discuss recent advancements or case studies can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the field through platforms like LinkedIn or relevant conferences. Making connections can provide insights into the company culture and potentially lead to referrals.
✨Tip Number 4
Prepare to showcase your programming skills, particularly in Python and libraries like TensorFlow or PyTorch. Consider working on a small project that demonstrates your ability to apply statistical methods and machine learning techniques.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Master-Thesis Student (all genders) in our Biomarker Statistics Team
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description for the Master-Thesis Student position in the Biomarker Statistics Team. Understand the responsibilities and required skills, especially regarding AI techniques and statistical analysis.
Tailor Your CV: Customize your CV to highlight relevant experience in statistics, machine learning, and any projects involving Python or AI concepts. Emphasize your academic background and any practical experience that aligns with the job requirements.
Craft a Compelling Cover Letter: Write a cover letter that showcases your motivation for the role and how your skills align with the team's objectives. Mention specific AI techniques or statistical methods you are familiar with and express your enthusiasm for contributing to clinical trial outcome predictions.
Highlight Communication Skills: Since the role requires good communication skills, provide examples in your application of how you've successfully worked in teams or communicated complex ideas. This can be through group projects, presentations, or collaborative research.
Wie du dich auf ein Vorstellungsgespräch bei Sanofi vorbereitest
✨Understand AI Techniques
Make sure to familiarize yourself with the AI techniques mentioned in the job description, such as HINT, SPOT, and LLM-based approaches. Being able to discuss these concepts and their applications in clinical trials will show your genuine interest and preparedness.
✨Showcase Your Statistical Knowledge
Prepare to discuss your understanding of key statistical and machine learning concepts. Be ready to provide examples from your studies or projects where you applied these techniques, especially using Python libraries like TensorFlow or PyTorch.
✨Demonstrate Communication Skills
Since the role requires good interpersonal skills, practice articulating your thoughts clearly and confidently. You might be asked to explain complex concepts, so being able to communicate effectively is crucial.
✨Research Sanofi's Values
Take some time to learn about Sanofi's mission and values. Understanding their commitment to improving lives through science will help you align your answers with their goals and demonstrate that you are a good cultural fit for the team.