PhD Student in Medical Science - Umeå, Sverige - Umeå University

Beskrivning

The Department of Diagnostics and Intervention announces a doctoral position in medical science with a focus on the development of new techniques for rehabilitation and functional impairments of injuries to the upper extremity supported by machine learning and neural networks. The position is an initiative within the framework of the research initiative "Learning and brain plasticity throughout the life span", which is one of Umeå University's prioritized research areas.

The employment period is four years and is intended to be full-time starting on or according to agreement.

You who are admitted to doctoral education will be part of the faculty-wide doctoral training program at the Faculty of Medicine. The program comprises 25 credits and is offered at two study paces: 25 credits over 8 semesters (a total of 4 years) or over 12 semesters (a total of 6 years), with program starts every autumn and spring semester. More information about the program can be found on the faculty's website for doctoral education (Doctoral education at the Faculty of Medicine - handbook )).

Job description and description of the doctoral project

The position aims at a doctoral degree and the doctoral student's main task is to engage in their own doctoral training, which includes participation in research projects as well as doctoral courses, journal clubs, seminars, etc.

The main goal of the project is to develop an AI system for rehabilitation of patients with impaired arm and hand function. At the hand surgery clinic in Umeå, patients with impaired function in their arm and hand are treated. This may include traumatic amputation injuries as well as congenital absence or underdevelopment of a part of the upper extremity, a condition sometimes referred to as dysmelia. Injuries to the arm's nerve plexus (plexus injury), or other nerves, can lead to a dramatic reduction in motor functions in the arm and hand.

Wireless sensors, for example based on surface EMG electrodes, gyroscopes, and accelerometers, are placed on the patient's arm to collect data about muscle activity and movements. AI models analyze this data and provide tailored feedback to the patient. The system can also be used to control advanced myoelectric prostheses. The expected result of this project is improved rehabilitation processes and increased functionality for patients with impaired arm and hand function. Additionally, increased user-friendliness and control of advanced myoelectric prostheses can be achieved.

The doctoral project will be designed together with the recruited doctoral student based on their undergraduate education and preferences, but may include the design and development of software and/or hardware, as well as experimental studies where we evaluate how well the developed system can improve patients' arm and hand function. The project will be based at the unit for hand and plastic surgery, at the Department of Diagnostics and Intervention to ensure that the development is patient-oriented, in close collaboration with Professor Tomas Nordström at the Department of Applied Physics & Electronics, and the Department of Medical and Translational Biology.

Admission requirements

To be admitted to doctoral education, the applicant must have both basic eligibility and special eligibility and be assessed as otherwise having the ability needed to cope with the education.

Basic eligibility

Basic eligibility for doctoral education is held by those who have completed a degree at an advanced level, completed course requirements of at least 240 higher education credits (ECTS), of which at least 60 ECTS are at an advanced level, or who in some other order within or outside the country have acquired substantially equivalent knowledge (Higher Education Ordinance 7 chap 39 §).

Special eligibility

To be admitted to doctoral education, the applicant must have the necessary knowledge from higher education or equivalent education and/or professional experience that is assessed in relation to the field of doctoral education and necessary language skills in English. Both written and oral skills are intended. Assessment of these skills is done by a prospective doctoral student presenting their research plan in English to an assessment group appointed by the head of the department.

Other qualifications:

The applicant should also have achieved basic theoretical knowledge in areas relevant to the project in their higher education, and/or in an equivalent manner, have good experience with laboratory work and method development. Experience in machine learning/deep learning, the most used ML frameworks (such as Keras or TensorFlow), the programming language Python, but also other programming skills and experience with software development, is highly meritorious. Experience in motion analysis and/or neurophysiology is desirable.