PhD/PostDoc/Internship opportunities

We are always looking to recruit excellent researchers, including UG and PhD interns, PhDs, and postdoctoral researchers to work with us on projects on computer vision for mobility impairments. If you are interested, feel free to drop a message to Dr. Gionfrida at letizia.gionfrida@kcl.ac.uk.

One funded MRC DTP PhD studentship on vision-based wearable robotic systems for activity recognition (OPEN)

Title: Vision in Soft Tactile for Contextual-aware Activity Recognition in Clinical Rehabilitation for Individuals with Cerebral Palsy

Project Description: Wearable robotics for clinical rehab relies on soft textile sensors for activity recognition. These cost-effective and discreet sensors outperform rigid ones in detecting human activities. To enhance their capabilities, we're integrating computer vision to gather context information, aiming to improve movement detection in clinical rehab. This can aid motor function recovery for conditions like stroke and Parkinson's disease, and extend to recognizing daily activities. You'll learn computer vision, and deep learning libraries like PyTorch, and work with clothing-embedded sensors. Yearly goals: (1) embed cameras in fabric for movement analysis, (2) categorize activities and terrains using motion data, (3) evaluate using vision techniques for accurate fabric movement assessment, with the ultimate goal of assessing behaviour and intention for tailored assistance.

The studentship will be in collaboration with Dr. Matthew Howard, Reader at the Centre for Robotics Research, Dr Adam Shortland, Reader in Clinical Biomechanics at Biomedical Engineering & Imaging Sciences, and  Professor Louise Rose, Head of Division, Applied Technologies for Clinical Care and Professor of Critical Care Nursing at King's College London.

To be considered for this opportunity, the ideal candidate should possess the following qualifications and skills:

More info here: https://kcl-mrcdtp.com/project/vision-in-soft-tactile-for-contextual-aware-activity-recognition-in-clinical-rehabilitation/ 

One half-funded PhD studentship to work on the MyoSuite (OPEN)

Title: Incorporation of High-level inputs in musculoskeletal simulator

Project Description: Current frameworks to investigate synergies in wearable robotics have emphasised the need for environmental awareness in musculoskeletal models to increase accuracy for unseen objects and tasks.6 Recently, MyoDex showed that low-level learned physiological representations share muscle coordination across tasks, which, like human synergistic control, facilitates learning across tasks.7 However, to synthesise new motor behaviours with environmental cues, higher-dimensional information (e.g., vision-tactile) for generalizability is needed. The proposed research aims to enhance dexterous assistive multi-finger manipulations by integrating high-dimensional real-world inputs, such as visuo-tactile information, into a physiologically accurate hand model to perform skilled manipulation tasks.

I am currently in search of potential collaborators who are open to sharing in the financial commitment of a 3.5-year tuition program, which amounts to a total of £52.5k. This partnership would extend throughout the entire duration of a student's involvement in the Myosuite project. It is worth noting that we extend this invitation to companies of all sizes, regardless of their organizational scale.

Engaging in these collaborative endeavours necessitates the participating company's willingness to contribute 50% of the studentship's expenses, equating to a £52.5k commitment over the course of three years. It is important to highlight that co-funded iCASE projects are subjected to a meticulous evaluation process, overseen by peer review, upon submission.

For more comprehensive details regarding the iCASE call and how to get involved, please refer to the following link: iCASE Project Call.

One funded PhD position on computer vision for wearable robotic systems [CLOSED]

Title: Enhancing Upper Limb Mobility for Individuals with Impairments: Context-Aware Control of Wearable Robotic Systems

To be considered for this opportunity, the ideal candidate should possess the following qualifications and skills:

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