DC7 PhD offer in the consortium DONUT at Miguel Hernandez University of Elche: “Brain- Machine Interface (BMI) systems for closed-loop control of lower-limb robotic exoskeletons”

Spain                 ·               Full time

 

PAGE CONTENTS

• Job Information
• Offer Description
• Requirements
• Additional Information
• Work Location(s)
• Where to apply
• Contact

 

Job Information

Organisation/Company: Universidad Miguel Hernandez de Elche

Department: Research Institute of Engineering of Elche

Research Field: Engineering » Biomedical engineering

Researcher Profile: First Stage Researcher (R1)

Country: Spain

Application Deadline: 29 Feb 2024 – 23:59 (Europe/Madrid)

Type of Contract: Other

Job Status: Full-time

Hours Per Week: 37.5

Is the job funded through the EU Research Framework Programme?: HE / MSCA

Marie Curie Grant Agreement Number: 101118964

Is the Job related to staff position within a Research Infrastructure?: No

 

Offer Description

The European Doctoral Network for Neural Prostheses and Brain Research (DONUT) has the mission to provide a multidisciplinary and inter-sectoral network for young talented researchers. The ambition of the project is to serve as a springboard for the expansion of EU partners into the fast-developing Brain-Computer Interface (BCI) technology and connected scientific disciplines. The DN will leverage the complementary expertise of 7 academic beneficiaries and 8 associated partners from 8 EU countries, to guide its 10 doctoral candidates (DCs) to address and solve deep problems in brain research, development of different BCI applications and systems with the latest technological advancements.

 

PhD project description:

Current Brain-Machine Interfaces (BMIs) based on motor imagery still lack enough accuracy to provide a suitable control of lower-limb exoskeletons in a clinical environment. In addition, users need long training periods to be able to command these systems.

Objectives: The main objective is to design and develop new kinds of BMIs based on motor imagery for commanding lower-limb exoskeletons that have higher accuracies and require shorter training periods than current ones.

Approach: New strategies will be explored to decode motor imagery information from EEG signals, including deep learning techniques and transfer learning techniques, to get higher accuracies and shorten the training periods. In addition, new protocols will be designed to command exoskeletons from brain signals in order to use them in neurorehabilitation therapies for stroke or spinal cord injury patients with motor limitations.

 

Expected Results:

1. Motor imagery BMI that can be used by stroke or spinal cord injury patients with motor limitations to command lower-limb exoskeletons.
2. BMI that requires shorter training to get higher accuracies to command lower-limb exoskeletons.

 

Requirements

Research Field: Engineering » Biomedical engineering

Education Level: Master Degree or equivalent

Research Field: Computer science

Education Level: Master Degree or equivalent

 

Skills/Qualifications

Please carefully review the following requirements that candidates must meet for this individual DC7 project. Each requirement holds equal importance:

 

Scientific Skills and Research Experience:

• Familiarity with Brain-Computer Interface (BCI) technology.
• Signal processing skills (including EEG signals or other biosignals).
• Experience in Artificial Intelligence techniques, including deep learning and transfer learning.
• High programming skills in Matlab and Python languages.
• Proficiency in scientific writing, a crucial aspect of the PhD.
• Possession of a broad scientific background.

 

Educational Qualifications:

• Hold an MSc level degree in fields relevant to the individual project.

 

Language Proficiency:

• Exhibit a good command of English, both in written and spoken forms.
• While not mandatory, proficiency in the Spanish language is highly recommended to facilitate integration into the local university culture.

 

Team Collaboration:

• Comfort and willingness to work collaboratively in a group setting within the laboratory.
• Ability to contribute to common projects, share experimental results, and learn from colleagues.

 

Motivation:

• Display high motivation to actively participate in the 3-year PhD program leading to a doctoral degree.

 

Flexibility:

• Willingness to engage in mandatory secondments between members of the DONUT consortium.
• Ability to work independently when required.

 

Initiative and Proactivity:

• Demonstrate a proactive and highly initiative approach to tasks and challenges.

 

Preferred Experience:

• Previous experience in research labs will be highly valued.

 

Ensuring compliance with all these requirements is essential for successful consideration as a candidate for this PhD position.

 

Specific Requirements

• Master degree in electrical engineering, biomedical engineering, computer science or equivalent relevant master degrees.
• Strong background on biomedical engineering, signal processing, and artificial intelligence.
• Excellent track record of academic achievement and a strong interest in conducting original research and innovation.

 

Languages: ENGLISH

Level: Good

 

Additional Information

Benefits

The Doctoral Candidate will be employed according to the rules for Doctoral Candidates in MSCA Doctoral Network and the general regulations of the hosting institution. We offer a monthly gross employer cost of €3104.2, plus €600 mobility allowance, and if applicable, €495 family allowance, according to the EU MSCA DN contributions for Spain. This corresponds to gross salary of approx. €2800 (including mobility allowance), or €3180 in case of DC with family obligations, considered as a marriage or a relationship with equivalent status to a marriage recognised by the legislation of the country where this relationship was formalized, or in case of dependent children who are actually being maintained by the DC. During the calculation of the net income a deduction of some taxes need to be considered.

 

Eligibility criteria

• Recruited researchers can be of any nationality and must comply with the following mobility rule: they must not have resided or carried out their main activity (work, studies, etc.) in Spain for more than 12 months in the 36 months immediately before their recruitment date.
• Candidates may not already hold a doctoral degree and must meet the admission requirements for enrollment to doctoral studies at Miguel Hernandez University of Elche.
• The recruitee must be working exclusively on the project.

 

Selection process

To apply for this position, please send an e-mail to dc7@donut-project.eu and enclose in a single PDF file:

• Curriculum vitae* (feel free to use Europass model, with contact information for 2-3 references).
• Cover letter in which you describe your motivation and qualifications for the position. Additionally, include in the motivation letter your plan of action specific for the position.
• Full list of credits and grades of both BSc and MSc degrees (as well as their transcription to English if possible)
• Short statement if your application may also be considered for other positions within the DONUT consortium.
• Proof of English proficiency (TOEFL, IELTS, CAE, TELC, …) – if available.
• Two reference letters – if available.
• Brief description of your MSc thesis.

 

* The curriculum vitae must be signed by the candidate and has to bear the following sentence concerning the management of candidate’s personal data: “The undersigned Name and Surname authorizes the management of his/her personal data contained in the application documents as foreseen by the European Regulation 2016/679 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data and declares to be aware of the rights of the data subject as listed in Chapter III of the aforementioned European Regulation”.

A recruitment committee will select suitable candidates for a first round based on academic formation, professional and/or research experience, motivation, and references. If selected, you will be given a short assignment related to the topic of the project to evaluate analytical abilities and level of written English, followed by interviews. Interviews will take place online to provide equal opportunities to all candidates independent of their location.

 

Additional comments

Miguel Hernández University of Elche (UMH) is a public young dynamic university, placed in the Southeast of Spain, a high economical and enterprising potential area. UMH is an advanced university equipped with the most modern infrastructures and technological equipment that make it possible to be strong in research.

The DONUT consortium embraces inclusion and diversity as key values. In the recruitment process measures will be taken to ensure that equal opportunities criteria in the selection process are applied, irrespective of gender, disability, marital or parental status, racial, ethnic or social origin, colour, religion, belief, or sexual orientation. In case of disability, a special needs allowance is available from the EU (so-called special needs allowance) to ensure adequate participation in the action.

 

Work Location(s)

Number of offers available: 1

Company/Institute: Miguel Hernandez University of Elche

Country: Spain

State/Province: Alicante

City: Elche

Postal Code: 03202

Street: Avda. de la Universidad s/n.

Geofield

 

Where to apply

E-mail: dc7@donut-project.eu

 

Contact

State/Province: Alicante

City: Elche

Website: https://www.umh.es/, https://bmi.umh.es/

Street: Avda. de la Universidad s/n

Postal Code: 03202

E-Mail: jm.azorin@umh.es

Phone: +34966658902