Understanding the Maynooth University Doctoral Scholarship at the Hamilton Institute

The Maynooth University Faculty of Science and Engineering Doctoral Scholarship, offered at the Hamilton Institute, presents a significant opportunity for aspiring researchers. This fully funded doctoral program is designed for individuals keen on exploring cognitive computational neuroscience, decision-making processes, neural network modeling, and human brain research. The scholarship provides a chance to work with experts in a leading research environment, helping scholars develop advanced skills in computational modeling, empirical research, and scientific writing.

Scholarship Overview

This doctoral scholarship is a four-year, fully funded program set to begin in September or October 2026. It is associated with the Hamilton Institute and will be supervised by Dr. Peter Murphy from the Department of Psychology. The project, titled “Identifying the Neurocomputational Basis for Making Decisions Abstracted from Sensation and Action,” aims to investigate how the human brain makes abstract decisions without relying on direct sensory input or motor actions. This research combines fields like cognitive neuroscience, psychology, artificial intelligence, and computational modeling.

Benefits of the Scholarship

The Maynooth University Doctoral Scholarship offers a comprehensive package for its recipients. This includes an annual student stipend of €25,000, covering living expenses. Additionally, full tuition fees are covered for the entire four-year duration of the program. Scholars will receive valuable research training through Maynooth University’s Graduate Research Academy. The program also provides opportunities to present research findings at various conferences, both locally and internationally, and offers support in preparing work for peer-reviewed journal publications. Recipients gain practical experience in areas such as neural network modeling, EEG studies, and computational neuroscience.

Research Project Details

The core of this research project is to understand the brain signals that show how information is gathered over time, leading to decisions that are not tied to immediate sensory experiences or physical actions. The PhD research will follow three main paths:

Trained Neural Networks

This part of the research will focus on identifying the specific conditions under which abstract information accumulation can be observed in neural networks. It seeks to understand how these networks learn to process information in a way that leads to abstract decision-making.

Biologically Constrained Network Modelling

Here, the project will explore how plausible neural mechanisms might be implemented through computational models. These models will be informed by biological data, aiming to create a more realistic representation of brain functions related to decision-making.

Empirical Testing in Humans

The final direction involves validating the predictions made by the computational models. This will be done through experiments with human participants, using behavioral data and electroencephalography (EEG) measurements to observe abstract decision signals in real time.

Responsibilities of the PhD Student

The successful candidate will be expected to actively contribute to the research. Key responsibilities include conducting computational research using neural network models, designing and analyzing both EEG studies and behavioral experiments, and managing research data according to FAIR principles. The student will also present findings at conferences and local meetings, and prepare manuscripts for publication in academic journals. Undertaking relevant training and participating in research development programs are also part of the role. The position requires the ability to work both independently and collaboratively under the guidance of supervisors.

Mode of Study

This is a full-time, four-year program requiring residency at Maynooth University in Ireland. The research will primarily take place on the Maynooth University campus. Any research conducted outside the campus requires prior permission from the supervisor and the Head of Department. The scholarship is subject to the general terms and conditions of the Maynooth University Doctoral Scholarship and the regulations of the Research Student Programme.

Eligibility Criteria

To be considered for this scholarship, applicants must meet certain essential requirements. These include holding a first-class or upper second-class (2.1) honors undergraduate degree in a relevant field such as Neuroscience, Cognitive Science, Computer Science, Psychology, or a related discipline. Prior independent research experience in areas like deep learning, neural networks, behavioral data analysis, or EEG studies is necessary. Proficiency in quantitative analysis and strong written and oral communication skills in English are also essential.

Desirable qualifications can further strengthen an application. These include a Master’s degree in a relevant field with a substantial research component, strong computational skills in programming languages like Python or MATLAB, and familiarity with neural network platforms such as TensorFlow or PyTorch. Experience with GPU or cluster-based computing, as well as hands-on experience with human psychophysics and scalp EEG studies, would also be beneficial.

Application Process

Interested candidates must submit a complete application package. This includes a personal statement, no more than 600 words, detailing their motivation and relevant experience. A Curriculum Vitae (CV) is also required, outlining education, research experience, quantitative and computational skills, and any publications. Applicants must also provide relevant academic transcripts and the names and contact details of two academic referees.

Applications should be sent via email to Dr. Peter Murphy at [email protected]. The subject line of the email must be clearly stated as: Doctoral Scholarship - Hamilton Institute/Psychology 2026. The deadline for submissions is 5 pm on July 1, 2026. Applicants who are not native English speakers will need to provide proof of their English language proficiency. Shortlisted candidates will be invited for an interview.

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