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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.
As a doctoral student you will join our research group at the Marianne Bernadotte Center within the Division of Eye and Vision at the Department of Clinical Neuroscience. The overall goal of our research is to use measurements of eye and vision to understand the workings of the human brain in both health and disease, and to improve our knowledge of how the visual system develops and functions across the life span. Most of our research involves eye tracking, typically in a clinical context with a neurological condition or cognitive deficit in focus. Our team is interdisciplinary, which means that you will get to work closely with colleagues with expertise from different scientific fields (e.g., optometry and ophthalmology, psychology, computational linguistics and more).
Vision is a highly active process and our eyes never stop moving. Even when we attempt to fixate our gaze on a steady visual target, we make small eye movements beyond our awareness commonly known as fixational eye movements. Microsaccades, the largest type of fixational eye movement, have long been of interest in eye movement research and visual neuroscience, in part because they are largely beyond volitional control and produced without the observer’s awareness, and in part because their functional significance to human vision has proven difficult to explain. Furthermore, in the past two decades a surge of research has shown that microsaccades are related to many aspects of visual perception, attention, and cognition, and thus potentially carry important information about brain function and neurological disease.
The purpose of this research project is to use machine learning methods to advance our understanding of fixational eye movements and how this type of eye movements may be affected by neurological conditions. The project will draw on recent advances in both reinforcement learning and supervised machine learning to better understand the spatiotemporal dynamics of these eye movements, as well as to identify early risk markers that might be useful in screening for neurodegenerative diseases.
It is not a requirement to be skilled in both reinforcement learning and supervised learning to apply for the position. A highly motivated applicant who has experience in only one of the two methodologies (reinforcement learning or supervised learning) will have the opportunity to learn the other during the project. As a PhD student in this project, you will record and analyze eye tracking data, design and implement machine learning workflows and computational models in Python, and perform statistical analysis in R and/or Python. You will be trained in all parts of the scientific process and actively be involved in all aspects of the research project, including planning, setting-up and running experiments, as well as writing manuscripts and publishing and presenting research findings in scientific journals and at international conferences.
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 (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:
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.
We are looking for a highly motivated PhD student who is interested in learning more about the fascinating relationship between the eye, vision, and the brain. We believe that you hold a degree in computer science, cognitive science, or psychology (or a related field dealing with computation and/or the human mind). You have an interest in how artificial intelligence (AI) and machine learning can be combined with sensor technologies, such as eye tracking, to learn more about the human nature. If you think you match this profile, you are particularly encouraged to apply.
In order to succeed in this role, we believe that you have:
In addition, it is an advantage, but not essential, if you have:
Moreover, it is important that you can work independently and take great responsibility for your own work tasks while also cooperating well with others. Your overall suitability for pursuing a doctoral education will be considered when filling the position.
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.
Read more about the research group here
Choose to work at KI – Ten reasons why
Type of employment | PhD placement |
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Contract type | Full time |
First day of employment | According to agreement |
Salary | Monthly salary |
Number of positions | 1 |
Full-time equivalent | 100 |
City | Stockholm |
County | Stockholms län |
Country | Sweden |
Reference number | STÖD 2-1097/2023 |
Contact |
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Union representative |
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Published | 14.Mar.2023 |
Last application date | 25.Apr.2023 11:59 PM CEST |