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Karolinska Institutet

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Karolinska Institutet postdoctoral scholarship

Postdoctoral Scholarship in Renal Epidemiology at Karolinska Institutet Karolinska Institutet in Sweden

Degree Level

Postdoc

Field of study

Computer Science

Funding

Scholarship funded postdoctoral position; amount is tax free, set for twelve months at a time and paid out on a six-month basis. The scholarship can be granted for up to two years within a four-year period following the doctorate; shorter periods may be acceptable in exceptional cases.

Deadline

Nov 5, 2026

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Country

Sweden

University

Karolinska Institutet

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Keywords

Computer Science
Data Science
Nephrology
Biostatistics
Cardiology
Biology
Medical Science
Salud Pública
Observational Study
Omics
Real-world Data
Kidney Disease
Statistics
ML

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About this position

Postdoctoral Scholarship in Renal Epidemiology at Karolinska Institutet (Location: Flemingsberg, Sweden).

This opportunity is hosted by the Division of Renal Medicine within CLINTEC and focuses on interdisciplinary research at the intersection of renal epidemiology, biostatistics, observational studies, clinical prediction modelling, and real-world data analysis. The successful postdoctoral researcher will work with patients with chronic kidney disease using the Swedish Renal Registry and other well-characterised clinical cohorts, including biopsy material, biomarkers, and patient-reported outcomes.

Research tasks include developing study protocols and statistical analysis plans, conducting registry-based observational studies, analysing multi-omics data and imaging-derived features from PET, CT, MRI, and ultrasound, applying machine-learning and AI-based methods, performing advanced statistical analyses including target trial emulation, and writing manuscripts and conference presentations.

Eligibility highlights: applicants must be foreign researchers coming to Sweden for postdoctoral education; they must hold a doctoral degree or equivalent in biostatistics, epidemiology, public health, data science, or a related field. Strong experience in real-world clinical data analysis, survival analysis, reproducible workflows, and proficiency in R and/or Python are required. Experience with multi-omics, radiomics, machine learning, international collaboration, and English scientific communication is highly desirable.

Funding: scholarship-based support, tax free, granted for twelve months at a time and paid in six-month instalments. The scholarship may be awarded for up to two years within a four-year post-PhD window.

Application window: apply by 5 November 2026 via the Varbi recruitment system. Required documents include a complete CV, publication list, and a one-page summary of current work.

Funding details

Scholarship funded postdoctoral position; amount is tax free, set for twelve months at a time and paid out on a six-month basis. The scholarship can be granted for up to two years within a four-year period following the doctorate; shorter periods may be acceptable in exceptional cases.

What's required

Applicants must be foreign researchers coming to Sweden for postdoctoral education and cannot be resident in Sweden or have carried out all or part of their academic education in Sweden. Candidates must hold, or have completed before the start date, a doctorate or equivalent degree in biostatistics, epidemiology, public health, data science, or a related discipline. Required experience includes real-world clinical data analysis, observational study design, survival analysis, clinical prediction modelling, and proficiency in R and/or Python with reproducible data-management workflows. Experience with multi-omics, radiomics, machine learning or AI-based methods, a strong publication record, international collaboration, and clear English communication are highly desirable; nephrology or cardiology experience is an advantage.

How to apply

Apply through the Varbi recruitment system no later than 5 November 2026. Submit a complete CV, a full publication list, and a summary of current work (max one page) in English or Swedish.

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