Doctoral Scholarship at Maynooth University’s Hamilton Institute Offers Deep Dive into Decision-Making
Maynooth University’s Faculty of Science and Engineering, in collaboration with the Hamilton Institute, is offering a fully funded doctoral scholarship for 2026. This opportunity is ideal for highly motivated students interested in cognitive computational neuroscience, decision-making processes, neural network modeling, and human brain research. The scholarship provides a chance to work with leading experts in a top-tier research environment, developing advanced skills in computational modeling, empirical research, and scientific writing.
This four-year program, starting in September or October 2026, focuses on a specific research project: “Identifying the Neurocomputational Basis for Making Decisions Abstracted from Sensation and Action.” The scholarship aims to support a PhD candidate in exploring how the human brain makes decisions that are independent of immediate sensory input or motor actions. This interdisciplinary project combines insights from cognitive neuroscience, psychology, artificial intelligence, and computational modeling.
Scholarship Benefits and Research Focus
The Maynooth University Doctoral Scholarship offers significant benefits to its recipients. It includes an annual student stipend of €25,000 and covers full tuition fees for the entire four-year duration of the program. Beyond financial support, the scholarship provides extensive research training through Maynooth University’s Graduate Research Academy. Scholars will have opportunities to present their findings at various conferences, both locally and internationally, and will receive guidance in preparing their research for publication in peer-reviewed journals.
The research project itself is designed to investigate the brain signals involved in accumulating information over time, which allows humans to make decisions independent of direct sensory or motor cues. The PhD research will explore three main avenues:
Trained Neural Networks
This area focuses on identifying specific conditions under which abstract information accumulation can be observed in trained neural networks. Researchers will explore how these networks process and integrate information to form decisions without relying on direct external stimuli.
Biologically Constrained Network Modelling
This part of the project aims to understand the potential neural mechanisms underlying abstract decision-making. It involves creating computational models that are informed by biological data and principles, investigating how these models can replicate observed brain functions.
Empirical Testing in Humans
The final direction involves validating the predictions made by the computational models. This will be achieved through behavioral experiments and electroencephalography (EEG) studies conducted with human participants, measuring abstract decision signals to confirm model findings.
Responsibilities and Study Mode
The successful PhD student will be responsible for conducting computational research using neural network models, as well as designing and analyzing behavioral and EEG studies. Data collection, management, and analysis will need to adhere to FAIR principles (Findable, Accessible, Interoperable, Reusable). The student will be expected to present research findings at conferences and local meetings, and to contribute to the preparation of draft publications for academic journals. Engaging in relevant training and research development programs is also a key responsibility.
The mode of study is full-time, requiring residency at Maynooth University in Ireland for the four years. Research activities 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 terms of the Maynooth University Doctoral Scholarship and the regulations of the Research Student Programme.
Eligibility and Application Requirements
To be eligible for this scholarship, applicants must hold 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. Essential qualifications include independent research experience in areas like deep learning, neural networks, behavioral data analysis, or EEG studies. Proficiency in quantitative analysis and excellent written and oral communication skills in English are also required.
Desirable qualifications include a Master’s degree in a relevant field with a substantial research component, strong computational skills in Python or MATLAB, and familiarity with neural network platforms like TensorFlow or PyTorch. Experience with GPU or cluster-based computing, as well as human psychophysics and scalp EEG studies, would be advantageous.
Applicants must submit a personal statement (maximum 600 words) detailing their motivation and experience, a Curriculum Vitae (CV) outlining their education, research experience, skills, and publications, and relevant academic transcripts. They also need to provide the names and contact details of two academic referees. Applications should be emailed to Dr. Peter Murphy at Peter.Murphy@mu.ie with the subject line: “Doctoral Scholarship – Hamilton Institute/Psychology 2026.” The deadline for applications is 5 pm on July 1, 2026. Non-native English speakers must provide proof of English proficiency. Shortlisted candidates will be invited for an interview.
