Doctoral student (PhD) position in computational pathology and medical artificial intelligence Full-time

Doctoral Student (PhD) Position In Computational Pathology And Medical Artificial Intelligence

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 Department of Medical Epidemiology and Biostatistics conducts research in epidemiology and biostatistics across a broad range of areas within biomedical science. The department is among the largest of its type in Europe and has especially strong research profiles in psychiatric, cancer, reproductive, pediatric, pharmaco, genetic, and geriatric epidemiology, eating disorders, precision medicine, and biostatistics.

The research group offers a highly interdisciplinary and vibrant research environment at the international forefront of developing and implementing precision medicine strategies for improving diagnostics and treatment of cancer. The doctoral position is hosted at the Department of Medical Epidemiology and Biostatistics (MEB), located at the Solna campus of Karolinska Institutet in Stockholm.

AI and machine learning (ML) provide new opportunities for precision medicine, where data-driven approaches are applied for improved diagnostics, prognostication and treatment decisions. One of the medical disciplines that are becoming increasingly data-driven is pathology, where digital scanning of tissue samples is becoming a routine practice and provides vast amounts of image data usable as the basis for more efficient and accurate clinical management of diseases like cancer.

The doctoral student will work in projects analyzing the performance of both in-house developed state-of-the-art AI models and publicly available foundation models in prostate cancer diagnosis, grading and prognostication across diverse patient populations and digital pathology platforms. The student will develop foundation models and AI algorithms for emerging solutions to streamline the clinical histopathology workflow, including agentic AI systems that support diagnostic and prognostic decision-making, with the aim of making precision medicine approaches in pathology more accurate, scalable and cost-effective.

The doctoral student is expected to build an in-depth understanding of state-of-the-art AI and image analysis methodology and to absorb a necessary level of medical and histopathological knowledge while working as a part of an interdisciplinary team of scientists and clinicians. The position of a doctoral student involves taking an active role in driving your own research projects, with guidance from the supervisor team, and in preparing scientific research articles for publication.

Choose to work at KI-Ten reasons why Career support for doctoral students International staff

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.

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

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

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

1. have been awarded a second-cycle/advanced/master qualification (i.e. master degree), or
2. 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
3. have acquired substantially equivalent knowledge in some other way in Sweden or abroad.

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

*If you claim equivalent knowledge, follow the instructions on the web page Assessing equivalent knowledge for general eligibility for doctoral education.

B) Specific eligibility requirement 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.

Follow the instructions on the web page English language requirements for doctoral education.

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) and (B) can only be certified by the documentation requirement for doctoral education.

The applicant is expected to possess the following skills and experience:

• A Master's degree or equivalent qualifications (see “Eligibility requirements”) in a field relevant for computational pathology, for example bioinformatics, biomedical engineering, biotechnology, computer science, image/signal processing, medicine, software engineering, statistics or related fields.
• A solid understanding of the basics of ML/AI (e.g. based on a suitable educational background or prior professional experience) and an interest in building a deep understanding of the theory and practice of ML/AI.
• Good programming skills in at least one programming language, preferably demonstrable in the form of sample code or other output from earlier projects/studies (e.g. link to Github/Gitlab profile).
• Fluency in written and spoken English.

The following skills and experience are considered meriting:

• Experience of working with digital pathology data and familiarity with whole slide image file formats and tools (e.g. OpenSlide, Bioformats, QuPath, Cytomine).
• Experience of working with other (biomedical) image data from e.g. microscopy or medical imaging systems.
• Knowledge of PyTorch and/or other AI and image analysis frameworks (e.g. TensorFlow, OpenCV, MATLAB).
• Strong programming skills in Python.
• Software engineering skills, including e.g. version control, dependency management and software testing.
• Experience of high-performance computing (e.g. using cloud, compute clusters or supercomputers).
• Expertise in data management, databases and registries.
• Knowledge of and interest in pathology, oncology or other relevant medical fields.
• Demonstrated scientific writing skills (e.g. in the form of theses or publications).
• Experience of working in an interdisciplinary setting and communicating with professionals from different backgrounds.

We attach great importance to personal qualities in this recruitment. The applicant should possess excellent analytical problem-solving skills, be able to show initiative and take responsibility for their research projects, and face obstacles in their work with perseverance. The applicant must also be highly collegial and be able to work well as a member of a cross-disciplinary and diverse team.

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)

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.