PhD and Postdocs Jobs at Trinity College Dublin in Ireland

Title: Doctoral Position (PhD Studentship) in NO-CANCERNET

Post Status: Full-time

Research Group / Department / School: Creagh research group, School of Biochemistry & Immunology, Trinity College Dublin, the University of Dublin

Terms & Conditions: €34,812 per annum plus mobility (€600/month) and family allowances (€660/month for researchers with a family), subject to deductions and taxes as per EC rules for Marie Sklodowska Curie Doctoral Networks 2022

Hours of Work: Full-time position for 3 years, starting June 2024 or earlier

Closing Date: 29.02.2024

Summary: The NO-CANCERNET PhD Studentship is part of a Marie Sklodowska-Curie funded Doctoral network aimed at fostering a new generation of leaders dedicated to advancing the treatment of triple-negative breast cancer (TNBC). This interdisciplinary, intersectoral, and international doctoral training and research programme encompasses a collaborative six-country network, including universities, government organizations, companies, hospitals, and cancer institutions. The Doctoral Candidate will investigate the role of inflammatory caspases in NO production and signalling during TNBC, with objectives including the validation of diagnostic markers, influence on NO production, and the development and assessment of a TNBC model in mice. The project involves secondments at prestigious European institutions.

Eligibility & Qualifications: Prospective candidates should hold an MSc degree (or BSc with a minimum 2.1 grade and additional lab-based research experience) in biochemistry, molecular biology, immunology, or related disciplines. Fluency in English and trans-national mobility requirements must be met.

Skills & Competencies: Desired skills include basic techniques in biochemistry, molecular and cellular biology, microscopy, primary cell culture, and experience with animal models is desirable but not essential.

Application Procedure: Applications should include a motivation letter, an up-to-date CV, and contact details of three referees, submitted via the specified Google Application form by the closing date. Informal enquiries can be directed to Dr. Emma Creagh (ecreagh@tcd.ie) for the specific post at Trinity College Dublin, and general enquiries about the NO-CANCER-NET network to NOCancerNet@universityofgalway.ie.

This opportunity offers a competitive salary, allowances, and the chance to be part of a groundbreaking project with significant implications for cancer treatment, within one of Ireland’s leading universities renowned for its commitment to research excellence and innovation.

Title: PhD Studentship in Biomedical Engineering

Post Status: Specific Purpose Contract – Full-time

Department / School: Academic Unit of Neurology, School of Medicine, Trinity College Dublin, the University of Dublin

Salary: €25,000 annual stipend for four years funded by the Trinity Research Doctorate Award, with EU and non-EU tuition fees covered

Hours of Work: 39 hours per week, Full Time, to commence 1st September 2024

Deadline: 15.04.2024

Summary: This PhD studentship, funded by the Trinity Research Doctorate Award for four years, invites applications from motivated candidates to join a project investigating neuroelectric signalling changes in Amyotrophic Lateral Sclerosis (ALS) using high density electromyography (EMG) and electroencephalography (EEG). The successful candidate will employ dimension reduction techniques and nonlinear dynamic measures to analyze high density EMG signal structures, with the goal of detecting early signs of motor unit dysfunction in ALS. The project includes phases of refinement and testing with simulated and healthy participant data before application to ALS patient data. The position is housed within the dynamic EXG Research Group at the Trinity Biomedical Sciences Institute’s Academic Unit of Neurology, offering rich interdisciplinary collaboration and expert guidance in ALS research.

Responsibilities include selecting appropriate analytical techniques, refining and testing EMG signal parameters, processing and analyzing EEG and EMG signals, assisting with data collection, managing datasets, and contributing to the research community through meetings, conferences, and publications.

Qualifications: Candidates should have or expect to obtain a first or upper second class honors degree in Engineering (Neural, Biomedical, Electronic/Electrical), Mathematics, Physics, Computational Neuroscience, or a related quantitative discipline. Essential qualities include a strong interest in biomedical/neural engineering and neuroscience, excellent analytical skills, and good coding ability (e.g., Julia, MATLAB, Python). Desirable qualities include experience in signal processing, particularly EMG and EEG analysis, experience with datasets, analytics, machine learning techniques, and a solid understanding of neuromuscular physiology.

Application Procedure: Applicants should submit a cover letter (detailing relevant experience/skills and motivation), transcripts and degree certificates, a full CV, and evidence of English language proficiency if required, to Ms. Kristal MacNamara at KMACNAMA@tcd.ie. Please include “Application for Trinity Research Doctorate PhD Position” in the subject heading. Specific queries can be directed to Dr. Lara McManus at LMCMANU@tcd.ie.

Note: Garda vetting will be required for successful candidates, and international applicants may need to provide Police Criminal Records Checks from countries where they have lived for six months or more.

Title: Research Fellow in Clinical Microbiology

Post Status: Specific Purpose Contract – Full-time

Research Group / Department / School: Clinical Microbiology, School of Medicine, Trinity College Dublin, the University of Dublin

Salary: Appointment on the International University Salary scales at PD1 scale €42,781-€49,177 per annum, in line with Government Pay Policy

Hours of Work: 39 hours per week

Closing Date: 01.03.2024

Summary: The project “Bridging the gap between environment and patient; investigating the risk and transmission of antifungal resistance in Aspergillus fumigatus” (GAP-AFR) focuses on the global concern of antifungal resistance, particularly azoles in Aspergillus fumigatus, affecting vulnerable patient groups. The emergence of multi-azole resistant A. fumigatus genotypes worldwide necessitates the development of surveillance systems. This multi-national effort, led by Wageningen University & Research, Netherlands, aims to understand and manage antifungal resistance epidemiology and evolution. The project will develop tools for detecting dual-use antifungal resistance and propose risk assessment strategies, incorporating air sampling surveillance across various geographies.

Duties and Responsibilities:

• Coordinate sample collection and processing.
• Conduct laboratory tests, including fungal culturing, antifungal susceptibility testing, DNA isolation, PCR, qPCR, and sequencing.
• Manage the local database of samples and study findings.
• Collaborate with project stakeholders and staff at TCD and St James’s Hospital.
• Disseminate research findings through presentations and publications.
• Support supervision/teaching of students and contribute to grant applications.
• Engage in departmental and college activities.

Funding Information: Funded by The Joint Programming Initiative on Antimicrobial Resistance (JPIAMR) and the Health Research Board for the Irish segment.

Person Specification:

• PhD in microbiology, molecular biology, or a related field.
• Experience in microbiology, preferably with A. fumigatus, and familiarity with molecular microbiology techniques.
• Skills in communication, management, and organization.

Application Procedure: Submit a full CV and contact details of 2 referees to Dr. Alida Talento (Alida.FeTalento@childrenshealthireland.ie).

This position offers an exciting opportunity to contribute to a critical area of medical research, aiming to tackle the global challenge of antifungal resistance within a leading academic and clinical environment.

Title: Research Fellow

Post Status: Specific Purpose Contract – Full-time

Research Group / Department / School: Gillan Lab, Trinity College Dublin, the University of Dublin

Location: Trinity College Institute of Neuroscience, Trinity College Dublin, College Green, Dublin 2, Ireland

Salary: €43,371 per annum (Researcher Salary Scale point 2, in line with Government Pay Policy)

Hours of Work: 9:00 AM – 5:30 PM

Closing Date: 01.03.2024

Summary: The Gillan Lab at Trinity College Dublin is seeking a Research Fellow to join an innovative project funded by the Health Research Board. The project aims to develop passive smartphone metrics for tracking cognitive fluctuations, targeting both the general population and specific patient groups, including psychiatric populations and those with Lewy body dementia. This role offers the opportunity for significant input into the research design within the scope of utilizing smartphone data to study dynamic changes in cognition.

Responsibilities:

• Data cleaning and aggregation of passive sensor data time series, development of novel analysis methods, and validation.
• Uphold highest security and privacy standards as per Trinity College Dublin’s policies.
• Guide a research assistant in data collection from clinical populations, including Lewy body dementia, ensuring the acceptability and suitability of mobile sensing for these groups.
• Engage in public and patient involvement activities, including workshops for feedback on mobile sensing applications.
• Attend lab meetings, collaborate with lab members, and participate in international conferences.
• Potential light teaching opportunities and encouragement to apply for independent research funding.

Qualifications:

• PhD in psychology, cognitive neuroscience, computer science, or a related field. Additional experience required if PhD is outside psychology.

Experience and Skills:

• Essential: Experimental design, handling large unstructured datasets, time series analysis, dissemination (publications, presentations), adherence to clear scientific practices, and foundational knowledge in mental health science.
• Desirable: Machine Learning.
• Strong data analysis skills with proficiency in Python, R, or similar, along with inferential statistics.

Application Procedure:

• Submit a full CV, including names and contact details of 2 referees, via the provided Google Form. Informal enquiries to Dr. Claire Gillan (gillancl@tcd.ie).

This Research Fellow position offers an exceptional opportunity to contribute to groundbreaking research in cognitive fluctuations using passive smartphone metrics, within a supportive and dynamic lab environment at Ireland’s leading university.

Title: Research Fellow (Postdoctoral)

Post Status: Specific Purpose Contract – Full-time

Research Group / Department / School: Distributed Systems Group, Discipline of Networks and Distributed Systems, School of Computer Science and Statistics, Trinity College Dublin

Salary: IUA Post-Doctoral Researcher Level 2A/B pay scale (€42,783 to €54,965 per annum), commensurate with experience and achievement

Hours of Work: 39 hours per week, full-time

Closing Date: 01.03.2024

Summary: The ClearWay project, funded by Science Foundation Ireland, is recruiting a Research Fellow to explore deep reinforcement learning (RL) and swarm intelligence for optimizing traffic with autonomous and conventional vehicles. The project aims to extend deep RL and swarm intelligence in cyber-physical systems, focusing on decentralized, multi-agent algorithms for system-wide traffic optimization. This role is an opportunity to contribute to state-of-the-art advancements in machine learning applied to intelligent transportation systems.

Duties and Responsibilities:

• Review and analyze research in deep RL and swarm intelligence.
• Develop, implement, and evaluate novel algorithms for traffic optimization.
• Undertake system development, integration, and large-scale simulation studies.
• Disseminate research findings through academic publications and presentations.
• Assist with project management, including monitoring project milestones and deliverables, and ensure compliance with project budgets and policies.

Funding Information: Funded by Science Foundation Ireland as part of the ClearWay project.

Person Specification:

• PhD in Computer Science, Computer Engineering, Electronic Engineering, or a related field.
• Expertise in machine learning, particularly deep and/or reinforcement learning.
• Strong software engineering and programming skills.
• Experience in generating new ideas and innovative solutions.
• Established track record of publication in relevant fields.
• Desirable: Experience in intelligent transport systems, distributed computing, optimization, and working with diverse stakeholders.

Skills & Competencies:

• Research, data analysis, and project management skills.
• Excellent communication and organizational abilities.
• Experience in working with international and multi-cultural teams.
• Ability to manage dynamic workloads and prioritize effectively.

Application Procedure: Email applications to vinny.cahill@tcd.ie and ivana.dusparic@tcd.ie with “ClearWay Fellowship” in the subject line, including:

1. A cover letter.
2. Curriculum vitae with details of qualifications, experience, and publications.
3. A 1-2 page research proposal.

This Research Fellow position offers the chance to work at the forefront of machine learning applications in traffic optimization, within a leading research institution renowned for its contributions to computer science and intelligent transportation systems.

Title: Research Fellow in Pharmacy (MIDAS)

Post Status: Specific Purpose Contract – 60% FTE

Research Group / Department / School: Discipline of Public Health and Primary Care, School of Medicine, Trinity College Dublin, the University of Dublin

Salary: Appointment on the IUA Postdoctoral scale, PD2 Point 1

Hours of Work: 60% Full-Time Equivalent

Closing Date: 08.03.2024

Summary: The MIDAS trial, focusing on Medicines and Social Prescribing to Address patient priorities in multimorbidity, seeks a Research Fellow to lead elements of the GP based pharmacists’ intervention. This mixed methods researcher will support practice recruitment, data collection and analysis, study governance, and dissemination of findings. The role demands a pharmacist with health services research experience, capable of engaging with clinical colleagues in general practice settings, and adept in both qualitative and quantitative research methods.

Duties and Responsibilities:

• Ensure delivery of the GP Pharmacist intervention component of the MIDAS cluster RCT.
• Support recruitment and training of practices across Ireland.
• Recruit, train, and oversee intervention delivery personnel.
• Facilitate collection and analysis of qualitative and quantitative data.
• Contribute to the MIDAS Process Evaluation and Health Economic Evaluation.
• Present findings at national and international conferences.
• Engage in manuscript preparation and submission.
• Assist in study governance and project operational management.

Funding Information: Funded by the Health Research Board of Ireland.

Person Specification:

• Qualification in Pharmacy with the ability to work clinically in community settings in Ireland.
• PhD or equivalent research experience in a related health science field.
• Experience in Health Services Research/Population Health research, ideally in general practice.
• Skills in research budget development and management.
• Excellent communication, organizational, and project management skills.
• Experience in RCTs, EU clinical trials directive, Irish Health Research Regulations, and data management and analysis is desirable.

Application Procedure: Submit a full CV, including the names and contact details of 2 referees, to Prof Susan Smith via phpcadmin@tcd.ie. Informal inquiries can be directed to Prof Susan Smith (susmith@tcd.ie) or Prof Andrew Murphy via una.stjohn@nuigalway.ie.

This position offers a unique opportunity to contribute to a significant health services research project aimed at improving care for patients with multimorbidity, within a leading academic setting.