1-2 doktorander i beräkningspatologi och medicinsk artificiell intelligens

1-2 doctoral students in computational pathology and medical artificial intelligence

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 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

We offer 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 Northern Stockholm. The group is affiliated with the national Data Driven Life Sciences (DDLS) program and SciLifeLab, providing the student with networking and career development opportunities as a member of the DDLS Research School.

We work closely together with other groups at MEB within and beyond the department’s prostate cancer research environment, as well as with academic and industry collaborators on national and international levels. This provides ample opportunities for establishing cross-disciplinary connections and collecting international experience during the doctoral education, for example in the form of attending conferences or conducting research visits to other universities.

The doctoral student project and the duties of the doctoral student

AI and machine learning (ML) provide new opportunities for precision medicine, where data-driven approaches are applied for improved diagnostics, prognostication and treatment decisions. 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 algorithms for new emerging solutions enabled by AI for streamlining the clinical histopathology workflow.

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 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.

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.

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.

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.

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

- A Master’s degree or equivalent qualifications 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 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.
- 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.
- 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.
- Strong programming skills in Python.
- Software engineering skills, including version control, dependency management and software testing.
- Experience of high-performance computing.
- Expertise in data management, databases and registries.
- Knowledge of and interest in pathology, oncology or other relevant medical fields.

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 of 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.

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. 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
- Documents certifying your specific eligibility

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.

All applicants will be informed when the recruitment is completed.

Want to make a difference? Join us and contribute to better health for all

Type of employment: PhD placement

Contract type: Full time

First day of employment: According to agreement

Salary: Monthly salary

Number of positions: 2

Full-time equivalent: 100

City: Stockholm

Country: Sweden

Contact:

- Union representative: Ann Almqvist, SACO, ann.almqvist@ki.se

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