PhD grant at Universidad Politécnica de Madrid

BIOMARKERS FOR THE DIAGNOSIS AND EVALUATION OF PARKINSON'S DISEASE BASED ON SPEECH AND OCULOGRAPHIC MULTIMODAL STUDIES
Laboratories:  Bioengineering and Optoelectronics Research Group
http://www.byo.ics.upm.es 
Doctoral school:  ETSI Telecomunicación, Universidad Politécnica de Madrid 
Discipline:   Neuroscience, machine learning, digital signal processing 
Supervision:  Juan Ignacio Godino Llorente 
Keywords:  Parkinson’s disease, speech, oculographic signals, multimodal evaluation, early detection 
Research context:   
This thesis project is placed in the context of the BIOMARKERS FOR THE DIAGNOSIS AND EVALUATION OF PARKINSON'S DISEASE BASED ON SPEECH AND OCULOGRAPHIC MULTIMODAL STUDIES (DPI2017-83405-R), financed by the Spanish Ministry of Economy and Competitiveness. 
Summary of the project:
Parkinson's disease is a chronic degenerative disorder affecting the dopamine production centers in the basal ganglia and which is mainly manifested with dysfunctions in motor systems. The disease affects 2% of the population over 60 years but its prevalence is likely to increase due to the aging trend of the world population. In addition to affecting the quality of life of patients and their environment, the disease carries a loss of productivity and high costs for health systems, so early diagnosis and treatment are vital to alleviate these negative effects. However, to date, there are not early and noninvasive markers of the disease. The literature has identified that voice and oculographic signals are affected even in pre-symptomatic stages, but this has not been exploited to design robust diagnosis and screening systems. Therefore this project aims at employing voice and oculographic signals as biomarkers for the design of automatic detection and screening systems based on digital signal processing techniques. To do this a phonetic-articulatory analysis of speech together with an analysis of eye movements (saccades, fixations, smooth pursuit...) analysis will be performed. The project objectives are relevant to the challenge 'health, demographic change and wellbeing' aiming at alleviating the cost associated with the disease on the European healthcare system. 
Candidate profile:  
We are looking for dynamic, creative, and motivated candidates with scientific curiosity, strong problem solving skills, the ability to work both independently and in a team environment, and the desire to push their knowledge limits and areas of confidence to new domains. The candidate should have a Master in Bioengineering, Computer Science, Acoustics, Electronic Engineering, Multimodal Interfaces, or Signal Processing, and experience in signal processing, machine learning, and information retrieval from complex data. A strong interest in bioengineering and multi-disciplinary applications is necessary.   It is not expected that the candidate will have already all the skills necessary, but a willingness and ability to rapidly step into new domains. 
Summary of conditions:
 Full time work (37,5h/week)  Contract duration: 4 years.  Life Insurance.  Estimated Incorporation date: Beginning of 2019.   Specific conditions of the call  
Application: 
Interested candidates should send a CV, transcript of Master’s degree courses, a cover letter (limit 2 pages) detailing their motivations for pursuing a PhD in general and specifically the project described above, and contact information for 2 references that the selection committee can contact. 
Application deadline:       
Complete candidature files should be submitted to ignacio.godino@upm.es before October 10th, 2018.
See also http://www.byo.ics.upm.es/BYO/noticias/phd-position