项目介绍

2024年11月16日

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 division of Neuro at the Department of Clinical Neuroscience is seeking a doctoral student to join Tobias Granberg’s Research Group, a specialized multidisciplinary group focusing on advanced neuroimaging applications comprising of about 30 members. This group integrates the clinical and experimental expertise of neuroradiologists, neurologists, MRI physicists and data scientists, forming a dynamic interdisciplinary team. We collaborate closely with various departments throughout Karolinska Institutet and Karolinska University Hospital, all of whom bring invaluable practical experience and specialized knowledge to our projects.

The doctoral student project and the duties of the doctoral student

The doctoral project will investigate the potential of Photon-Counting Computed Tomography (PCCT) in neuroimaging, particularly as an alternative to Magnetic Resonance Imaging (MRI) for volumetric analysis of the brain in populations where MRI accessibility may be limited. The project will assess the accuracy, variability, and clinical relevance of CT-based volumetry techniques compared to MRI standards, focusing on key brain structures, including grey matter, white matter, and intracranial volumes. Through a combination of atlas-based and deep-learning methods, such as CTseg and SynthSeg, the study aims to validate PCCT’s effectiveness in neuroanatomical segmentation, potentially offering a cost-effective solution for widespread clinical use. The project aims to develop a machine learning-based volumetric analysis technique tailored for PCCT, specifically designed for integration into clinical workflows to enhance accessibility and precision in neuroanatomical diagnostics.

The doctoral student will be responsible for data acquisition, segmentation analysis, and validation of the volumetric findings against MRI-based data, leveraging specialized software like FreeSurfer, SPM12, and advanced machine learning models for imaging analysis. They will manage a dicom library and data server, support network and enterprise connectors, interpret volumetric results, explore correlations with cognitive scores, and support a streamlined design for the clinical applicability of PCCT-based techniques. Furthermore, the student will contribute to interdisciplinary clinical discussions, present findings in scientific forums, and work toward the implementation of PCCT in clinical workflows under their supervisors’ guidance. This project aims to enhance diagnostic accessibility and accuracy, particularly for patients requiring neuroimaging investigation.

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 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.

Skills and personal qualities

We are seeking a PhD student with a medical background and strong experience in neuroimaging and related research. Ideal candidates will have the following:

• Background and proficiency in the field of neuroradiology (MRI and PCCT).
• Background in machine-learning and developing multi-modal pipelines.
• Experience with medical software and application development.
• Databasing, particularly with a strong background in drafting/managing SQL libraries by linking dicom metadata with neuroradiological/clinical data from Swedish Registries.
• High degree of experience working with dicom metadata and extracting dicoms tags to sort and run quality assurance of large-scale real-world clinical data.
• Neuroimaging data organization into a dynamic BIDsified format.
• Special consideration is given for a medical/clinical background, due the multi-disciplinary nature of the project and the end goal of implementing the tool into a clinical setting.
• Experience in Linux server management and command-line proficiency, network maintenance, and administration of network-based storage across multiple sites, including collaboration with industry partners.
• Strong computational processing background, including expertise in: dockerized environement; resource management; python, image processing, linux commandline and OS admin.
• Good knowledge of English both written and spoken.

Terms and conditions

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