Intern (m/f/x) Artificial Intelligence (Munich, BY, DE) bei Europe | Daiichi Sankyo
Europe | Daiichi Sankyo · Munich, Deutschland · Onsite
- Optionales Büro in Munich
Passion for Innovation. Compassion for Patients.
With over 120 years of experience and approximately 19,000 employees in more than 30 countries/regions, Daiichi Sankyo is dedicated to discovering, developing, and delivering new standards of care that enrich the quality of life around the world.
In Europe, we focus on two areas: The goal of our Specialty Business is to protect people from cardiovascular disease, the leading cause of death in Europe, and help patients who suffer from it to enjoy every precious moment of life.
In Oncology, we are driving innovation in solid tumours and blood cancers, founded on breakthrough science from our own labs in Japan. We aspire to create better tomorrows for people living with cancer and their loved ones.
Our European headquarters are in Munich, Germany, and we have affiliates in 15 European countries and Canada.
For our headquarters in Munich we are seeking highly qualified candidates to fill the position:
Intern (m/f/x) Artificial Intelligence
The Position:
This internship offers an opportunity to engage with cutting-edge research in Causal Inference using Machine Learning (ML), focusing on advanced methodologies including, but not limited to, Doubly Robust Learners and Double Machine Learning (Double ML) using Bayesian Additive Regression Trees (BART) and other machine learning methods. By leveraging flexible ML techniques for modeling both treatment assignment and outcomes, these methods aim to correct for complex, non-linear confounding biases, thereby enabling more precise estimation of causal effects such as Average Treatment Effects (ATE), Conditional Average Treatment Effects (CATE), and Individual Treatment Effects (ITE).
Roles and Responsibilities:
- Conduct a comprehensive review of existing ML-based causal inference methods, assessing their suitability for different types of causal effect estimation and data characteristics.
- Evaluate state-of-the-art causal inference techniques on benchmark datasets and contribute to the development of a robust toolkit for causal inference in evidence generation.
- Implement and apply Double ML methods, with a focus on conducting sensitivity analyses to assess robustness of causal estimates.
- Prepare and deliver a presentation summarizing findings and insights to the team.
Personal Skills and Professional Experience:
- Basic causal inference knowledge: propensity scores, IPW estimators, propensity score matching, observational data, ATE, etc.
- Familiarity with machine learning and Data Science methodology.
- Interest in diving into causal inference using Machine Learning techniques.
- Skilled in Python programming for Data Science and Machine Learning.
- Some R programming experience.
- Strong analytical and problem-solving skills.
- Excellent communication skills with a proficient English level.
- Ability to work effectively in a collaborative team environment.
- Strong attention to detail and the ability to manage and organize data.
Why work with us?
Working at Daiichi Sankyo is more than just a job – it is your chance to make a difference and change patients’ lives for the better. We can only achieve this ambitious goal together. That is why we foster a culture of mutual respect and continuous learning, with a strong commitment to inclusion and diversity. Here, you will have the opportunity to grow, think boldly, and contribute your ideas. If you have a proactive mindset and passion for addressing the needs of patients, we eagerly await your application.
For more information: www.daiichi-sankyo.eu
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