wo vacatures in Hoogmade

PhD Position in Causal Inference and Big Data

max. € 3.939,- 36 hours Master degree Fixed term contract

You have 12 more days to apply

Join us in advancing causal inference and machine learning to transform patient care. As a PhD candidate, you will work with healthcare data from over 20 million people and become an expert in state-of-the-art causal inference methods, uncovering how treatments can be personalized for cardio-kidney-metabolic diseases. You'll be part of a collaborative, international team where technical curiosity, mentorship, and shared ambition drive both scientific discovery and better outcomes for patients.

About your role

As a PhD candidate, you will push the boundaries of causal inference and machine learning to improve care for patients with heart failure, chronic kidney disease, and type 2 diabetes, collectively known as cardiovascular-kidney-metabolic (CKM) syndrome. You will play a key role in optimizing the use of powerful new treatments like GLP-1 receptor agonists and SGLT-2 inhibitors, which have revolutionized the field but require further exploration to fully understand their benefits in everyday clinical practice. In your work, you will use recent breakthroughs in causal prediction modeling and causal machine learning to estimate treatment benefits on an individual level, using large-scale healthcare data from millions of individuals.

Your core tasks will include:

• Develop and apply advanced causal inference methods (e.g., target trial emulation, causal machine learning).
• Analyze large-scale healthcare datasets from more than 20 million patients in the Netherlands (CBS, ELAN) and Sweden (SCREAM).
• Collaborate with clinicians to translate technical insights into clinical impact.
• Present research findings at international conferences and publish in high-impact journals.
• Work with leading investigators at institutions like the Karolinska Institute, UCSF, and Harvard, with opportunities to spend part of your PhD abroad.

This PhD position offers the unique opportunity to be at the forefront of a transformative research area, while making a tangible impact on improving healthcare for patients with CKM syndrome.

About your workplace

You will join the CareMeds Lab (CArdio REnal MEtabolic Data Science) at the Department of Clinical Epidemiology. We are a multi-disciplinary and collaborative team with a clear mission: to improve care for patients with CKM diseases by combining high-quality data with cutting-edge causal inference methods. Our research has shaped more than ten international clinical guidelines (e.g. KDIGO 2023 guideline on CKD Evaluation and Management). Beyond clinical impact, we have inspired researchers across diverse fields to adopt novel causal inference methods, such as target trial emulation. At the same time, we believe great science thrives in a friendly, informal environment and we enjoy regular social activities.

About you

You are a motivated and passionate individual with a strong background in data science, (bio)statistics, epidemiology, computer science, or a related field. You are driven by the opportunity to apply your technical skills to make a real difference in healthcare. You enjoy working in an international, interdisciplinary environment, where collaboration and learning are key to success. You thrive in a dynamic setting and are eager to expand your knowledge in causal inference, machine learning, and big data analytics.

Your qualifications include:

• A background in data science, (bio)statistics, epidemiology, computer science, or a related field.
• Proficiency in programming (preferably in R or Python), with a keen interest in working with large datasets.
• A strong eagerness to learn about causal inference, machine learning, and big data analytics, with training and daily supervision provided by Dr. .
• An ability to collaborate effectively within an international and interdisciplinary team, contributing your technical expertise to meaningful healthcare outcomes.

Our offer

Driven by health; that's our mission. This applies not only to our patients but also to our employees. We strive to provide a safe, inclusive and equitable work environment, with a focus on talent development and connected leadership. In order to be able to continue to learn and develop, we offer internal and external training. You are also entitled to an end-of-year bonus (8,3%), holiday allowance, sports budget, bicycle scheme, home office allowance and an excellent commuting allowance. Furthermore, as an employee of LUMC, you are also affiliated with the ABP pension fund. This means that 70% of your pension premium is paid by LUMC, leaving you with a higher net salary. Nice, right?

What do we represent?

As an academic medical center, LUMC strives to have a workforce that is a good reflection of society. We are committed to the highest quality in health care, education and (international) research, in which diverse perspectives are essential. Sustainability is also a high priority for us: we are committed to a healthy future, not only for people, but also for the planet. In line with these values, we aim to be a creative and inspiring place to work, where everyone feels at home, safe and valued. It's all about who you are and what you bring to contribute, regardless of your background. Together, we work toward a sustainable and inclusive future, both for the people around us and for the world we live in. Together, we are LUMC.

• As a Ph-candidateD, your salary will be between €3,108 and €3,939 gross per month (scale PRO, CAO UMC). These figures are based on a full-time position.
• The selection process consists of three rounds: the submission of a CV and motivation letter, followed by an in-person meeting to get acquainted with the project and the team at LUMC, and lastly a presentation on a scientific article (also attended online by the international members of the team).
• The employment will start as soon as possible (first quartile of 2026) and has a maximum duration of four years. The position begins with a temporary appointment of one year. If progress is satisfactory, the contract will be extended to a total of four years.
• Applications from employment/recruitment agencies will not be considered.

SGLT-2 inhibitors, GLP-1 receptor agonists, and DPP-4 inhibitors and risk of hyperkalemia among people with type 2 diabetes in clinical practice: population based cohort study

Sodium-glucose cotransporter 2 inhibitors vs. sitagliptin in heart failure and type 2 diabetes: an observational cohort study

Starting right: aligning eligibility and treatment assignment at time zero when emulating a target trial

Target Trial Emulation to Improve Causal Inference from Observational Data: What, Why, and How?

Timing of dialysis initiation to reduce mortality and cardiovascular events in advanced chronic kidney disease: nationwide cohort study