control engineering | Scholarship for Nigerians and Africans

Graduate Student Positions in the Area of Biological/ Biomedical Signal Processing and Mathematical Modeling, Singapore-MIT Alliance for Research and Technology (SMART), Singapore

We are recruiting PhD students for projects within the Singapore-MIT Alliance for Research & Technology (SMART), to be supervised by MIT and NTU faculty. In those projects we apply mathematical engineering to problems in bioengineering and biochemistry, for example:

o Bayesian modeling of parasitic life cycle
o large-scale graphical models for functional genomics
o stochastic modeling and control engineering in the context of tissue generation.

Please send detailed curriculum vitae, GRE/TOEFL scores, statement of research interests, three references, and relevant publications (if applicable) electronically to:

Prof. Justin Dauwels
Nanyang Technological University
School of Electrical & Electronic Engineering
Singapore
recruitment-at-dauwels.com

Scholarship Application Deadline: July 2011

Further Scholarship Information and Application

PhD Position at LIRMM-INRIA, Montpellier, France: Whole body control framework for lower limb stability in computational rehabilitation

INRIA is the French national institute for research in computer science and control. DEMAR project’s research interests are centered on the human sensory motor modeling, including muscles, sensory feedbacks, and neural motor networks.

research direction:
Identification of biomechanical dynamics and muscle dynamics for neurologically damaged patient is already challenging as the system
response can drastically vary depending on the degree of the patient deficiencies. In FES (Functional Electrical Stimulation), movement
synthesis and control are still a challenging task due to the complexity of whole body dynamics computation and the nonlinearity of
stimulated muscle dynamics. One of the challenge concerns the feedback (torque, EMG, joint angle) that can be used to control joint angle,
torque or stiffness. Moreover, control strategies have to be designed in order to be performed on portable architecture and tuned through
advanced modeling and simulation.
In this context, the goal of this PhD work is to study the optimization-based motion synthesis and real-time control framework
which can generate stimulation patterns from the pre-computed motion synthesis database. Motion capture system together with the estimation of the Center of Mass would be used to assess the strategies. This work aims at the development of automatic method to establish deficient limb stability in computer-aided rehabilitation.
This PhD work is performed under the collaborative project named @walk (artificial walking) between INRIA DEMAR project and AI lab of
Stanford University.

Research background:
-Master in control engineering, computer science, biomechanics, robotics or related disciplines.
– good knowledge of C/C++ programming and matlab.

Scholarship Application Deadline: Contact Employer

Further Scholarship Information and Application

PhD Position at LIRMM-INRIA, Montpellier, France: Whole body control framework for lower limb stability in computational rehabilitation

INRIA is the French national institute for research in computer science and control. DEMAR project’s research interests are centered on the human sensory motor modeling, including muscles, sensory feedbacks, and neural motor networks.

research direction:
Identification of biomechanical dynamics and muscle dynamics for neurologically damaged patient is already challenging as the system
response can drastically vary depending on the degree of the patient deficiencies. In FES (Functional Electrical Stimulation), movement
synthesis and control are still a challenging task due to the complexity of whole body dynamics computation and the nonlinearity of
stimulated muscle dynamics. One of the challenge concerns the feedback (torque, EMG, joint angle) that can be used to control joint angle,
torque or stiffness. Moreover, control strategies have to be designed in order to be performed on portable architecture and tuned through
advanced modeling and simulation.
In this context, the goal of this PhD work is to study the optimization-based motion synthesis and real-time control framework
which can generate stimulation patterns from the pre-computed motion synthesis database. Motion capture system together with the estimation of the Center of Mass would be used to assess the strategies. This work aims at the development of automatic method to establish deficient limb stability in computer-aided rehabilitation.
This PhD work is performed under the collaborative project named @walk (artificial walking) between INRIA DEMAR project and AI lab of
Stanford University.

Research background:
-Master in control engineering, computer science, biomechanics, robotics or related disciplines.
– good knowledge of C/C++ programming and matlab.

Scholarship Application Deadline: Contact Employer

Further Scholarship Information and Application