4 év / 8 szemeszter (nappali / levelező)
2 év / 4 szemeszter (egyéni)
állami ösztöndíjas / önköltséges
felvételi eljárási díj: 9000 Ft
240 kredit (tanulmányi/ kutatási kredit)
Entry requirements:
Oral exam (all applicants)
+ Complex exam (for Untrained program)
Application period:
Apr. 7. 2025 - May 31. 2025
Dec. 2025 - Jan. 2026 (cross-semester)
A tagozatról
The aim of the John von Neumann Graduate Program for Medical Data Science is to dedicate itself to providing advanced education and training in the interdisciplinary field of medical data science to students with an MSc in informatics, mathematics, physics, and medicine. It will oƯer a comprehensive curriculum designed to equip PhD students in medical data science with the skills and knowledge needed to excel at harnessing the power of data for healthcare innovation.
The graduate school will be a cross-university endeavor, with participating institutions including Semmelweis University, Eötvös Loránd University, Budapest University of Technology and Economics, and Ludwig-Maximilians-Universität München. This collaborative eƯort ensures a diverse and enriching educational experience, drawing on a broad range of expertise.
The Curriculum will be gradually built and rolled out and will incorporate (but not be limited to)
the following topical areas:
- Statistical Modeling of Multi-Modal Molecular Profiles in Longitudinal Health Studies
- Optimized Health Screening via Cost-Aware Multi-Modal Data Integration
- Machine Learning for Early Detection and Characterization of Multimorbidity
- Development of a Trusted Research Environment for Secure, Scalable Clinical Analytics
Years and semesters: Dr. Kosms Kepesidis plans to oƯer a 4-year-long program made up of 8 semesters but is open for the university’s suggestiton to shorten it with one year / two semestres to better fit the university’s other doctoral programs.
Teaching format: The program will only be available in a full-time format with hybrid teaching method (both onsite and remote classes and workshops).
Financing: The program is primarily self-financed. Hungarian students or foreign students fulfilling the necessary criteria can apply for a state scholarship. The Center for Molecular Fingerprinting, co-founder of the Institute plans on oƯering scholarships in the future. Any further financial necessities will be fulfilled based ont he agreement of the Semmelweis University and the Center for Molecular Fingerprinting.
Credits: Attainable credits will come from conducted and published researches and acadmic work. Total number of credits and their exact proportoins will be finalized later on. Dr. Kosmas Kepesidis plans on giving one course per semester to contribute to academic credits. He also would like to give the students a chance to particfipate in Dr. Roland Molontay’s courses in his master’s program in Biomadical Data Science.
Admission requirements: the point system of the Semmelweis university applies
- oral exam with Dr. Kosmas Kepesidis where he assesses the applicants’ English knowledge of his professional field, their interests, past work and achievements, capabilities, motivation, potention, etc.
- research plan (1-2 pages)
- all documentation otherwise requiered by the Semmelweis University’s Doctoral Schools (Master’s degree, grade of degree, list of publications, recommendation letter, etc.)
Program type: Traditional PhD program
Who can apply to the program: Individuals holding a M.Sc. in quantitative fields, such as statistics, mathematics, computer science, physics, or engineering.
Programs
01. Medical Data Science
Program Leader: Dr. Kosmas Kepesidis
Scope of the PhD Program: Computational and Statistical Foundations for Multi-Modal Molecular Health Profiling
As part of the John von Neumann Graduate Program for Medical Data Science, this PhD program oƯers a rigorous and interdisciplinary research training environment focused on the integration, analysis, and interpretation of complex molecular datasets for healthcare innovation. Drawing on the strengths of four leading academic institutions—Semmelweis University, Eötvös Loránd University, Budapest University of Technology and Economics, and Ludwig-Maximilians-Universität München—this program provides PhD candidates with access to world-class mentorship, data resources, and collaborative opportunities across institutions and disciplines.
The program is centered around the development and application of computational, statistical, and machine learning methods to multi-modal biomedical data, with a strong emphasis on real-world health applications and population-level insights. Students will work on one of four closely interlinked projects that contribute to a shared vision: leveraging advanced data science to redefine personalized health monitoring, early disease detection, and clinical decision-making.
Four Core Research Topics:
- Statistical Modeling of Multi-Modal Molecular Profiles in Longitudinal Health Studies
This project focuses on characterizing the natural variation in individual molecular profiles using longitudinal data from the H4H study. Students will work with FTIR spectroscopy, MS-proteomics, and NMR-metabolomics to quantify inter-individual variability, identify stable molecular signatures, and uncover hidden structure in high-dimensional datasets. The research aims to improve the understanding of biological fluctuation, enabling more personalized and preventive healthcare strategies. - Optimized Health Screening via Cost-Aware Multi-Modal Data Integration
Based on data from the ProHEALTH Pilot Study, this project will develop intelligent policies for selecting measurement modalities—balancing predictive power with cost-eƯectiveness. Through the fusion of MS-proteomics, NMR-metabolomics, and FTIR data into joint predictive representations, students will explore adaptive sampling strategies that enhance screening eƯiciency without compromising diagnostic quality. - Machine Learning for Early Detection and Characterization of Multimorbidity
This project investigates blood-based liquid biopsies and multi-modal omics to detect and understand complex patterns of disease progression in large cohorts (H4H and NAKO). Emphasizing non-invasive, scalable methods like FTIR spectroscopy, the research seeks to identify early phenotypic markers and systemic changes indicative of multimorbidity, providing key insights for precision medicine and public health. - Development of a Trusted Research Environment for Secure, Scalable Clinical Analytics
In response to the growing need for secure, federated data analysis platforms, this project will design and implement a Trusted Research Environment (TRE) tailored tolarge-scale clinical studies like the PPS. Students will contribute to the architecture and deployment of the TRE, supporting privacy-preserving analytics and enabling multi-institutional collaboration on sensitive health data.
Program Highlights:
- Interdisciplinary Curriculum spanning biomedical informatics, statistical learning, computational biology, and clinical applications.
- Cross-institutional supervision and training, oƯering a diverse and collaborative academic experience.
- Access to high-quality, real-world datasets from the H4H, NAKO, and PPS studies.
- Hands-on experience with cutting-edge tools in secure data environments, multi-modal integration, and interpretable machine learning.
Graduates of this PhD program will be equipped to lead data-driven innovations in biomedical research, healthcare delivery, and public health policy—shaping the future of medicine through the intelligent use of data.
Entry requirements
Who can apply for PhD training?
Those with a university degree (MSc, MA) can apply for PhD training (proof of education is not yet required in the admissions process, but studies can only be started with proof of education).
In case of proof of excellent research results, doctoral training can also be started with a bachelor's degree and started master's studies or in the last two years of the undivided studies.
Division, program and topic selection
When applying for doctoral training or obtaining a degree, it is mandatory to indicate the chosen doctoral division. The admission interviews are organized by the doctoral divisions. The program and topic selection are only mandatory from the second semester onwards (with the exception of individual degree holders and the Stipendium Hungaricum Scholarship applicants, who can only apply with the recommendation of the future supervisor/consultant).
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During an admission procedure, you can only apply for one division and have to indicate the topic and supervisor of a program.
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If the applicant does not wish to choose a program, supervisor and topic in the first semester, then the head of the doctoral division will be the student's supervisor during the first semester.
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Enrollment for the second semester can only be done by indicating the program, supervisor or topic approved by the doctoral school.
General admission requirements
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Doctoral applicants must be university graduates (MSc or MA degree) or students registered for their final semester of university studies, or Bsc graduates who started their MSc, as well with proven excellent research track
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Applicants for the English-Language PhD program must have a good command of English, which is assessed at the entrance interviews
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When applying to the program, applicants are required to state the specific training program and research topic they wish to pursue within one of the University’s doctoral programs
- The admission procedure is based on evaluating the candidate’s general and topic-related knowledge as well as personal ability, academic competence and previous scientific activity and contribution.
Admission requirements for Individual ("Untrained") Program
The PhD candidates in the untrained program are supposed to take a complex comprehensive exam after a successful entrance interview.
The exam has two parts:
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the practical part (students have to give a 8-10 minutes long presentation in front of the examination board)
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the theoretical part of the exam (1 main subject, 1 additional subject) - the Recommendation for the subjects of the complex exam and for the members of the professional board of the theoretical exam form is filled in by the Doctoral Divisions not by the students.
Kapcsolat - Neumann János Adattudományi Tagozat
Chairman: Dr. Kosmas Kepesidis
E-mail: kosmas.kepesidis@lmu.de
Phone: +49 89 289 54067
Educational coordinator:
E-mail:
Phone:
Why is it worth getting a degree with us?
- Innovation efforts at Semmelweis University are based on more than 250 years of tradition and professional experience.
- An opportunity to work at the Heart and Vascular Center, one of Europe’s leading institiutions.
- Our supervisors are all internationally recognised leaders in their field with extensive research networks.
- Access to grants, international contacts, and publishing in highly respected international journals.
- We provide an inspiring environment with a multidisclipinary approach, in which the researcher may experience a true scientific adventure of discovery.
How to apply
Application and admission periods
Application period
- in case of traditional training in April-May
- in case of cross-semester training in November-December
Dates of entrance exams:
- during spring application in June
- in the case of cross-semester enrollment at the end of January
How to apply?
The application can be submitted online after registration.
The application interface is only active during the admission process period.
Documents required for application
Documents have to be uploaded during the online application:
- Curriculum Vitae with detailed work/professional experience (1-2 pages)
- a photocopy of the university diploma(s),
- if a non-Hungarian diploma: an authenticated translation or its naturalisation document should be submitted,
- if required, the equivalence decision of the Hungarian Ministry of Education (of a non-Hungarian diploma)
- in case of application without MSc, MD etc. degree: Certification of the examination results, the credit certificate from Neptun
- proof of at least one intermediate state accredited language examination C type, or the certificate of an equivalent language examination, or certicate of the supervisor about the necessary English knowledge, or certificate of English language university studies
- in case of application for trained Phd program short research plan, which is the outlines of the selected research tasks if you apply for a specific theme attached to a particular supervisor (2-3 pages)
- list of publications (if you have any publications)
- proof of payment of the application fee
- documents which can certify the additional points (second degrees, awards, publications, etc.)
- in case of application for untrained Phd progam written recommendation of the supervisor/ consultant
(please note that the untrained Phd program is not available for the cross-divisional Translational Medicine program)
Payment of the application fee
Payment of the application fee is a condition for acceptance of the application for doctoral training.
- The admission fee is HUF 9,000 (except the applicants of the cross-divisional Translational Medicine Program in case of non-EU applicants or appilcants of the bilateral-program. In these cases please click here)
How to pay?
- by online card payment (by onlinebank card payment initiated from the registration interface via with Simple pay)
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by transfer, on the basis of an invoice (please upload the payment proof to the admission interface)
How to get an invoice?
If you choose bank transfer, please send the following information to the staff of the Financial Management Unit – Doctoral School (titkarsag.digh@semmelweis.hu) regarding the payment of the admission fee. Based on the data given, an invoice will be sent to the applicant, who can transfer the application fee by referring to this invoice.
When requesting an invoice for an individual person:
- applicant’s name, address,
- passport number,
- phone number,
- e-mail address.
When requesting an invoice for a company:
- name of applicant,
- company name,
- headquarter address,
- tax number,
- phone number,
- email address
- the company’s statement in email about whether it accepts electronic invoices
- the company’s signed, attached pdf statement about its bank account number.
If you choose to pay by bank transfer, please upload the payment proof to the admission interface, also send it to the staff of the Financial Management Unit – Doctoral School (titkarsag.digh@semmelweis.hu). Finalization of the application is possible only after uploading the payment proof.
Admission fee for the applicants of the cross-divisional Translational Medicine Program - non-EU or bilateral program
- The admission fee is EUR 75.
- Application fee can be paid via bank transfer, based on an invoice, which can be requested at tmk@semmelweis.hu.
If you choose to pay by bank transfer, please upload the payment proof to the admission interface, also send it to the staff of the Center of Translational Medicine (tmk@semmelweis.hu). Finalization of the application is possible only after uploading the payment proof.
Things to do before starting the studies
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Enrollment: enrollment takes place in person, at a pre-specified time (at the beginning of the first semester) in the Doctoral Office. Accepted students will be notified by e-mail of the exact date and the required documents. Attention, the condition for starting doctoral training is the presentation of a moral certificate not older than three months. Read more →
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Activating the Neptun semester and recording the subjects
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Applying for a student ID card
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In the case of self-funded students, payment of the tuition fee
- The students of the cross-divisional Translational Medicine Program have to sign a cooperation agreement involving the Center of Translational Medicine, the supervisor, the student, and the respective organizational unit.
Scholarships, tuition and other fees
About the Doctoral College