Doctoral student in equitable AI for breast cancer screening and risk prediction

Karolinska Institutet, doctoral positions

Solna kommun

On-site

SEK 357,000 - 469,000

Full time

13 days ago

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Benefits offered by this job

Salary as doctoral student (doctoral学生

Job summary

Karolinska Institutet invites applications for a doctoral student position in equitable AI for breast cancer screening and risk prediction. The project uses a large multi-region Swedish screening dataset and demographic data; you will develop and evaluate fair AI models and publish findings internationally.

You will be supervised by senior researchers and undertake epidemiology, biostatistics, machine learning, and AI fairness training as part of the doctoral education.

Qualifications

Master's degree (or equivalent) in bioinformatics, biostatistics, or a related quantitative field.
Programming skills for data processing and analysis.
Knowledge of statistical and epidemiological methods.
Strong analytical ability and interest in interdisciplinary research at the intersection of AI, medicine, and health equity.
Ability to work both independently and collaboratively in a multidisciplinary team.
Excellent written and spoken English.

Responsibilities

Take an active and increasingly independent role in study design, cohort construction and register linkage, statistical analysis, running and evaluating AI systems on imaging data, model development, writing scientific publications, and presenting results at international conferences.
Collaborate with the Computational Breast Imaging Group and external partners; contribute to equitable AI for population-based breast cancer screening.

Skills

Programming skills for data processing

Statistical methods

Analytical ability

Excellent English

Education

Master's degree in bioinformatics/biostatistics or related field

Job description

Doctoral student in equitable AI for breast cancer screening and risk prediction

Do you want to contribute to top quality medical research?

To be a doctoral student means to devote oneself to a research project under supervision of experienced researchers and following an individual study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required.

The research group

The doctoral student will be based at the Department of Oncology-Pathology , Karolinska Institutet, within the Computational Breast Imaging Group led by Associate Professor Fredrik Strand . The group is internationally recognized for the development and evaluation of AI for breast cancer imaging and precision medicine, combining expertise in radiology, machine learning, and biostatistics. It comprises PhD students, research engineers, research assistants, postdoctoral researchers, and collaborating senior clinicians in radiology, pathology, oncology, and surgery. The group has active national collaborations (KTH, Lund University, the Institute for Future Studies, and several groups at KI) and international collaborations (among others UC Berkeley, UCSF, University of Hawaii, and University of Barcelona). Available infrastructure includes high-performance computing, GDPR-compliant secure storage, and the VAI.B platform, which holds multi-region Swedish screening mammography data linked to cancer outcomes. The doctoral student will be supervised by Apostolia Tsirikoglou , PhD, research specialist and lead AI scientist in the group, as main supervisor, together with Associate Professor Fredrik Strand, head of the group and principal investigator of the project, as co-supervisor.

The doctoral student project and the duties of the doctoral student

This PhD project investigates whether AI systems used in population-based mammography screening perform equitably across population groups, and how inequities can be reduced. AI is entering breast cancer screening both as detection support and as risk prediction to guide screening intervals and supplemental imaging. Systems developed on specific populations may perform differently for groups that were underrepresented in their development, and screening outcomes already differ by country of birth and socioeconomic status. Evidence on equitable performance is therefore needed before AI is adopted at scale.

The project uses a large multi-region Swedish screening dataset with radiologist assessments, cancer outcomes from the National Quality Register for Breast Cancer, and demographic and socioeconomic data from Statistics Sweden.

The doctoral student will evaluate commercial and in-house AI cancer detection systems and AI risk prediction models across subgroups defined by country of birth and socioeconomic status, compare AI with radiologist performance in the same groups, and, in a later phase, develop and evaluate fairness-aware models that reduce identified disparities while maintaining clinical performance.

The doctoral student is expected to take an active and increasingly independent role in study design, cohort construction and register linkage, statistical analysis, running and evaluating AI systems on imaging data, model development, writing scientific publications, and presenting results at international conferences. The doctoral education includes courses in epidemiology, biostatistics, machine learning, and AI fairness. Where needed, competence in deep learning model development will be built during the project under supervision.

What do we offer?

A creative and inspiring environment full of expertise and curiosity. Karolinska Institutet is one of the world's leading medical universities. Our vision is to pursue the development of knowledge about life and to promote a better health for all. At Karolinska Institutet, we conduct successful medical research and hold the largest range of medical education in Sweden. As a doctoral student you are offered an individual research project, a well-educated supervisor, a vast range of elective courses and the opportunity to work in a leading research group. Karolinska Institutet collaborates with prominent universities from all around the world, which ensures opportunities for international exchanges. You will be employed on a doctoral studentship which means that you receive a contractual salary. Employees also have access to our modern gym for free and receive reimbursements for medical care.

Eligibility requirements for doctoral education

In order to participate in the selection for a doctoral position, you must meet the following general (A) and specific (B) eligibility requirements at latest by the application deadline.

It is your responsibility to certify eligibility on the Entry requirements (eligibility) for doctoral education web page.

A) General eligibility requirement You meet the general eligibility requirement for doctoral/third-cycle/PhD education if you:

have been awarded a second-cycle/advanced/master qualification (i.e. master degree), or
have satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the advanced/second-cycle/master level, or
have acquired substantially equivalent knowledge in some other way in Sweden or abroad.*

Follow the instructions on the Entry requirements (eligibility) for doctoral education web page.

You meet the specific eligibility requirement for doctoral/third-cycle/PhD education if you:

Show proficiency in English equivalent to the course English B/English 6 at Swedish upper secondary school.

Verification of your documents Karolinska Institutet checks the authenticity of your documents. Karolinska Institutet reserves the right to revoke admission if supporting documents are discovered to be fraudulent. Submission of false documents is a violation of Swedish law and is considered grounds for legal action.

A master's degree (or equivalent) in bioinformatics, biostatistics, or a related quantitative field
Programming skills for data processing and analysis
Knowledge of statistical and epidemiological methods
Strong analytical ability and interest in interdisciplinary research at the intersection of AI, medicine, and health equity
Ability to work both independently and collaboratively in a multidisciplinary team
Excellent written and spoken English

Desirable/advantageous:

Experience with population-based register data and record linkage, preferably Swedish national registers
Experience with cohort construction and subgroup analyses in large health datasets
Experience with large-scale processing of medical imaging data or evaluation of AI systems on clinical data
Interest in health equity, fairness in AI, and responsible implementation of AI in healthcare

Terms and conditions

The doctoral student will be employed on a doctoral studentship maximum 4 years full-time.

Submit your application and supporting documents through the Varbi recruitment system. Use the button in the top right corner and follow the instructions. We prefer that your application is written in English, but you can also apply in Swedish.

Your application must contain the following documents:

A personal letter and a curriculum vitae
Degree projects and previous publications, if any
Any other documentation showing the desirable skills and personal qualities described above
Documents certifying your general eligibility (see A above)
Documents certifying your specific eligibility (see B above)

Selection

A selection will be made among eligible applicants on the basis of the ability to benefit from doctoral education. The qualifications of the applicants will be evaluated on an overall basis.

Karolinska Institutet uses the following bases of assessment:

Documented subject knowledge of relevance to the area of research
Analytical skill
Other documented knowledge or experience that may be relevant to doctoral studies in the subject.

All applicants will be informed when the recruitment is completed.

KI applies a salary scale when setting salaries for doctoral students.

Apply at the latest 17 th November.

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Type of employment

Type of employment PhD placement

Contract type

Contract type Full time

First day of employment

First day of employment Up on Agreement

Salary

Salary Monthly salary