Fully Funded Research Masters Student Position in the Area of Hyperspectral imaging for biomedical applications using spectroscopy and machine learning Department of Electronic Engineering Maynooth University, Ireland

The Department of superposition Electronic Engineering at Maynooth University is pleased to announce that 1 Research Masters studentship is available with the start date of October 2023 in the area of hyperspectral imaging for biomedical applications using spectroscopy and machine learning

Open position	1 Research Masters Studentship in Hyperspectral Imaging
Location	Department of Electronic Engineering, Maynooth University
Duration	2 Years
Funding / Stipend	The position is funded for 2 years, including a monthly stipend and a travel budget to present at international conferences, workshops and seminars. The studentship will cover fees and a stipend of € 18,500 per annum.
Contact	Dr Bryan Hennelly (bryan.hennelly@mu.ie)
Closing/Start Date	Aug 18th 2023/Oct 1st 2023
Extension to PhD	Depending on performance, funding can be sought to extend to a full 4- year PhD

 

Key technology

Hyperspectral imaging using coherent Raman spectroscopy (CRS) is an advanced imaging technique that combines the principles of Raman spectroscopy and imaging. It allows for label-free, non-destructive, and high-resolution imaging of biological samples where the image can be tuned to visualise different chemicals in the tissue post-recording. In CRS-based hyperspectral imaging, two laser beams with different frequencies are used to excite molecular vibrations in the sample. The interaction be tween the laser light and the sample generates coherent Raman scattering signals, which provide molecular-specific information about the sample, allowing researchers to visualize and analyse its chemical composition and spatial distribution.

 Why is this technology important?

Hyperspectral imaging using CRS enables the visualization and characterization of specific molecules and their distributions within tissues or cells. It has the potential to revolutionise our insights into various biological processes, such as cell metabolism, tissue morphology, and disease progression. Hyperspectral imaging can differentiate between healthy and diseased tissues and can assist in detailed tissue analysis and pathology by providing information on cellular structures, chemical composition, and molecular changes associated with diseases. In surgical procedures, hyperspectral imaging can serve as a real-time imaging tool to guide surgeons by identifying tumour margins, distinguishing between healthy and diseased tissues, and optimizing the extent of tissue resection. Hyperspectral imaging using CRS can be valuable in drug discovery and development processes enabling researchers to study drug-target interactions, monitor drug delivery and distribution, and assess therapeutic efficacy at a molecular level.

General Research Theme of the Research Masters Project

The student will work on an exciting project involving a recently built laser system that performs hyperspectral imaging of tissue samples with unprecedented spectral resolution and fast capture rate. The student will be required to work closely with other team members responsible for building/maintaining/and using this system. The student will also become proficient in using and maintaining this system and will be required to learn about aspects of nonlinear optics and optical engineering including the use of opto-electronic instrumentation. The student will also be required to work closely with members of the biology department who will prepare and mount samples for imaging, and may be required to engage with the preparation of the samples. The student will need also need to communicate effectively with the biology staff as we seek to interpret the hyperspectral images that are captured. The main work of the masters student will be in the area of data capture and processing. The raw data will be heavily processed in order to produce images that are visually interpretable to the biologist. This process will require the student to become proficient in programming in python to work on aspects of machine learning as well statistical modelling. Overall the student will be exposed to aspects of biology, statistics, programming, machine learning, photonics and optical engineering.

 Research Masters Studentship

The position is funded for 2 years, including a monthly stipend and a travel budget to present the research outputs at international conferences, workshops and seminars. The studentship will cover fees and a stipend of € 18,500 per annum. The successful candidate will be enrolled on the Research Masters programme in the Department of Electronic Engineering at Maynooth University. The successful candidate will write their thesis supervised by Dr Bryan Hennelly, as well as a second supervisor from the Department of Chemistry, for the entire duration of their programme. The successful candidate will be an integral part of the overall research programme that Dr Hennelly is leading around the topic of biomedical microscopy and spectroscopy. The successful candidate will be prepared to work with Dr Hennelly’s network of collaborators who are among the leading scholars working on state of the art technologies in biology, imaging, spectroscopy, and mathematics.

 Duties and Responsibilities

1.      Undertake postgraduate research in the area of agreed research project.

2.      Work closely with the academic supervisors to ensure that the progress of the individual project is in line with the objectives of Dr Hennelly’s research programme.

3.      Work effectively within a multidisciplinary environment that includes, physicists, engineers, chemists, biologists and mathematicians.

4.      Attend and participate in all training events and supervisory meetings.

5.      Prepare progress reports.

6.      Present and publish research outputs to both academic and non-academic audiences.

7.      Attend and participate in academic and non-academic conferences, events and seminars.

8.      Contribute to teaching/training of undergraduate and postgraduate project students working with Dr. Hennelly’s group.

 As the description of the duties and responsibilities cannot be exhaustive, it is worth mentioning that the student may be required to undertake other duties that are broadly in line with the objectives of their research projects.

 Qualifications, Expected Skills and Competencies

1.      Applicants must hold at least a first or upper second-class honours Bachelor’s or Master’s degree in Engineering, Computer Science, or a related discipline.

2.      Strong mathematical, analytical and programming skills. Any experience in Python or deep learning would be desirable but is not required.

3.      An aptitude for machine learning.

4.      Any experience in PCA/LDA or similar multivariate statistical classification tools would be beneficial but not essential.

5.      Highly proficient English language skills.

6.      Excellent written and verbal communication, including presentation skills.

7.      Excellent organisational skills, attention to detail and the ability to meet deadlines.

8.      Ability to think logically, create solutions and make informed decisions.

9.      Willingness to work collaboratively in a research environment.

10.  A strong commitment to their own continuous professional development.

11.  The main thing we are looking for is someone who likes solving problems and likes maths.

 Application Process / Additional Information

Applications must be sent by e-mail to Dr Bryan Hennelly (bryan.hennelly@mu.ie). Early applications are strongly encouraged.

 Applications should include:

1.      A cover letter explaining the applicant’s motivation and interest in the project topic. Any relevant background and/or experience needs to be mentioned.

2.      A Curriculum Vitae that includes the applicant’s educational qualifications and any scientific publications and achievements.

3.      Academic transcripts.

4.      Two academic references.

 Informal enquiries concerning the advertised position, accompanied with the CV and a motivation letter, can be made to Dr Bryan Hennelly (bryan.hennelly@mu.ie).

 Applications will close at 5pm (GMT) Aug  18^th, 2023. The received applications will be analysed after the application deadline, and the shortlisted candidates will be invited to a Skype interview.