Do you want to help shape tomorrow’s healthcare with AI? As an intern at Pacmed you’ll spend your internship building models that improve decision making in healthcare every day. You’ll work on real clinical data alongside data scientists, engineers and clinicians.
At Pacmed we combine technology and humanity to keep healthcare accessible and future-proof. We are an AI company with software already running in multiple Dutch hospitals, and we are actively scaling further across the Netherlands. With our software, we help clinicians make better real-time decisions, use capacity more efficiently, and ensure smooth patient flows. As an intern you sit right at the point where our models and data meet clinical practice.
Why you’ll like interning here
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We’re a dynamic scale-up on a mission to keep healthcare accessible and future-proof.
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Your work is real: it goes into products used in hospitals, not into a drawer.
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You’ll have a supervisor who is invested in your growth, and a team that likes helping each other get better.
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We care about kindness and respect, and we like to have fun, with regular team events, quarterly outings and a yearly off-site.
The Capacity Monitor gives healthcare professionals AI-based predictions and insights based on real-time hospital data, so they can plan personnel and capacity proactively instead of reactively. On the ICU it forecasts patient occupation and burden of care ("zorgzwaarte"), translating expected patient numbers into the personnel capacity that is actually needed.
We are now extending the same approach to other departments on the acute care axis, where personnel planning is today largely not data-driven: the emergency department (SEH), the cardiac emergency department (EHH) and the cardiac care unit (CCU). In parallel we are exploring clinical-logistics use cases, such as automatic department overviews and patient-trajectory planning, to save coordinating nurses and doctors time and give them earlier, department-level insight from patient-level predictions they can override.
The Aftercare ("nazorg") Monitor targets one of the larger inefficiencies in Dutch hospitals: delayed and inefficient patient transfer out of the hospital. Patients who no longer have a medical reason to stay but cannot yet move on ("verkeerde bedden") account for an estimated 5–15% of bed days in the hospitals we work with. This blocks flow upstream (e.g. the emergency department and elective procedures), frustrates patients, raises complication risk, and drives unnecessary cost.
The module predicts, early and at the individual patient level, whether a patient will need aftercare and what their expected discharge date is. This enables the transfer team to prioritise which patients to screen first, and prompts ward doctors and nurses to arrange the discharge process in good time. The same data and models can be used to predict the number of patients flowing out to aftercare (VVT) institutions, so those institutions can manage their own capacity better. We are developing this together with hospitals.
The exact mix depends on your project, but as an intern you can expect to:
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Train and evaluate machine-learning models on real hospital data.
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Design and run retrospective and impact analyses that show, and improve, the clinical value of our products.
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Join sessions with clinicians to understand their workflow and translate it into modeling choices.
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See your work discussed in sprint planning and, where it lands, make its way into the product.
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Use AI tooling wisely and responsibly to help you in your work.
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Close supervision from an experienced data scientist, with real room to own your project.
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A substantial portfolio project on a genuine clinical-AI problem.
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An internship set up to fit your thesis or study requirements.
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First-hand experience of what it takes to build clinical AI and let it make impact.
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To be treated as a full member of the team from day one.
Recent interns have delivered work that fed directly into our products, for example our Burden of Care model.
We run intern projects across both products. The main projects are:
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Capacity Monitor: improving model performance for the ICU module using richer data from the next data iteration, and developing models for new hospitals and acute care axis departments: (cardiac) emergency department and the cardiac care unit.
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Capacity Monitor: clinical validation of our Burden of Care model in one or more hospitals.
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Aftercare Monitor: developing a model to predict patient outflow to long-term care (VVT) institutions.
We keep this list high-level here, because the exact scope depends on the match with your interests and skills.
We need several interns joining us over the coming months. The requirements are:
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Start date: starting between September and December 2026.
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Duration and availability: at least 6 months full time, or the equivalent part time (more than 50% of full time over a correspondingly longer period).
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Studies: the internship needs to be part of your Masters studies or PhD trajectory
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Data science skills: you are familiar with core data science principles and have some experience applying them, ideally in Python.
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Clinical affinity: affinity with Dutch hospital care is essential; hands-on experience is a big plus.
Depending on the specific project, we may need someone with deeper data science experience, more hands-on clinical experience, or fluency in Dutch, and we will discuss which of these matters most for your project during the matching process.
You’ll work mainly in Python, processing clinical data with pandas and Polars and training models with scikit-learn and related libraries. Around that sits our product stack (FastAPI, SQL, VueJS, Docker) on Azure, which you’ll meet when your work finds its way into the product. Nobody knows all of these on day one, and you’ll pick up plenty on the job.
We’re recruiting several interns for several projects, so we don’t hire for one fixed assignment. We get to know you first and then match you to the project that best fits your interests and skills. In practice this means a short introductory chat, a more in-depth conversation about your background and interests, and a joint decision on the project that fits you best.
Interested? Send us a short motivation and your CV and let us know your availability and study program.
- An internship compensation of €500 per month.
- Regular social events, with quarterly outings and a yearly off-site.
- Flexible working arrangements in working hours and (some) working from abroad.
- 25 paid holidays per year based on full-time employment (pro rata for part-time).
- Lunch provided daily at the office, with plenty of vegetarian and vegan options.
- Option to customise public holidays: swap some standard public holidays for alternative days to accommodate personal or religious observances.
- ️ A company laptop for the duration of your internship.
Start date: starting between September and December 2026.-
Duration and availability: at least 6 months full time, or the equivalent part time (more than 50% of full time over a correspondingly longer period).
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Studies: the internship needs to be part of your studies
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Data science skills: you are familiar with core data science principles and have some experience applying them, ideally in Python.
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Clinical affinity: affinity with Dutch hospital care is essential; hands-on experience is a big plus.
