MSc Studentship Position in Computational Inorganic Chemistry
Department of Chemistry, Maynooth University
A two-year research MSc is available in the Department of Chemistry at Maynooth University under the supervision of Dr. Tobias Kraemer.
The group’s research interests center around transition metal organometallic chemistry, main group and bioinorganic chemistry, as well as electronic structure and bonding. Quantum chemistry and theoretical spectroscopy are central in solving chemical problems related to these thematic areas. The successful candidate will use molecular simulation methods to study organometallic multi-step catalytic cycles in order to get insight into the mechanistic details of these reactions at the electronic structure level. The successful candidate will learn to use a wide range of state-of-the-art quantum chemistry methods, get insight into theoretical aspects of molecular modelling and gain proficiency in the application of DFT and ab initio methods to a range of problems drawn from the above thematic areas.
We are looking for highly motivated candidates, who have reached a high honours standard with a minimum 2:1 (or equivalent international qualification) primary degree in Chemistry or related discipline.
Prior experience with theoretical chemistry methods, Linux environments and/or computer programming would be an advantage, but is not a requirement.
Candidates must have excellent written and verbal communication and presentation skills in English.
Minimum English language requirements can be found at https://www.nuim.ie/study-maynooth/postgraduatestudies/courses/msc-chemistry#tabs-entry
Candidates who wish to apply should provide a CV and full academic transcripts, along with contact information of two academic referees.
Applications and enquiries about the position should be sent to: Dr. Tobias Kraemer Department of Chemistry, Maynooth University
Stipend: €8,000 per annum
Closing date: 31/03/2019
Departmental Website: https://www.maynoothuniversity.ie/chemistry/our-people/tobias-kr-mer#1
PhD Studentships in the Hamilton Institute for Mathematics, Communications and Computation
Applications are invited for a number of fully funded full-time EU PhD studentships available at Maynooth University (Ireland) in the area of Bayesian machine learning supervised by: Professor Andrew Parnell CStat, Hamilton Institute, Maynooth University
Research areas include: Bayesian additive regression trees, multivariate factor models, anomaly detection, and closed-loop control theory. Company partners include IBM and Clavis Insight. Further application areas include bioinformatics and environmental monitoring.
Candidate Profile: Applicants should be prepared to start between July and October 2018, and have a thorough grounding in Bayesian statistics and R.
Scholarship details: Each PhD studentship comprises a tax-free stipend of EUR18.5k over 4 years, a computing budget, and a generous travel allowance. All queries should be addressed to email@example.com.
The Hamilton Institute for Mathematics, Communications and Computation
Founded in 2001 with support from Science Foundation Ireland, the Hamilton Institute has been internationally recognized for its work across communication networks, mathematical biology and fundamental mathematics. Current areas of interest for the institute include the improvement of privacy in online systems, the application of probability to immunology and the enhancement of randomised network protocols. Graduate education has always been a core activity of the Hamilton Institute with 35 PhD students and 17 MSc (Research) students graduated since 2003. The institute, in collaboration with the Centre for Telecommunications Value Research (CTVR) in Trinity College Dublin, established the Network Mathematics Graduate Programme (funded under PRTLI 4) and was actively involved in the national Telecommunications Graduate Initiative (funded under PRTLI 5). Further information on the Hamilton Institute is available at www.maynoothuniversity.ie/hamilton
The Psychology Department has a range of research opportunities open to PhD and MSc prospective students. Please visit the Psychology Department website for more information.
Maynooth University is seeking an ambitious EU Marie Curie Early Stage Research to work as a contract employee. The candidate will enroll in the university's strucutred PhD programme under the supervision of Prof. Ken Duffy (Hamilton Institute). Tuitions fees will be covered by the programme. The salary will be set at €3,530 per month (Tax deductible). For more information please click on link.
Euraxess PhD Opportunity Eu Initial Training Network
National Centre for Geocomputation
U-Flyte Funded PhD Projects
U-Flyte Strategic Partnership
Funded by Science Foundation Ireland and involving collaboration with Industry partners including Airbus, Irelandia Aviation and Intel, U-Flyte is a R&D partnership, established to tackle the current global logjam impeding the wider development of drone operation and rollout of commercial services. The research work-plan is based around a series of inter-connected work-packages that deal with the development of novel airspace modelling tools and drone traffic management systems – also known as U-Space and Unmanned Traffic Management (UTM) systems. Advanced flight-testing is carried out at Waterford Airport and selected mobile locations across Ireland. Drone services including mapping, monitoring and logistics. Specialist aerial support services will also be developed and tested using real-world, end-use case scenarios. U-Flyte comprises Geospatial Scientists, Software Engineers, Mathematicians, Domain Specialists and Drone Operations personnel, working with the latest Vertical Take-off and Landing (VTOL) and hybrid drones, sensors (Optical, LiDAR, Navigation, Radar) and cloud computing resources. At the heart of U-Flyte is advanced computational expertise including autonomous navigation, Machine Learning and Geospatial Analytics all dedicated to developing the next generation of Beyond Visual Line of Sight (BVLOS) autonomous drone services.
U-Flyte now wishes to recruit PhD candidates to join this aerial robotics team based within the National Centre for Geocomputation (NCG), an established research centre at Maynooth University. We would especially like to hear from candidates with good primary degrees in Computing or Mathematics interested in developing careers in Aerial Robotics, Machine Learning, Computer Vision & Geospatial Data Analytics. If you feel you have the right background and want to know more – please get in touch.
- 3D Pathfinding & traffic management architectures for large-scale urban drone operations
This project focuses on the creation of new U-Space models & UTM systems designed to handle large numbers of autonomous drones carrying out a variety of data gathering, logistic and robotic activities in urban environments. This PhD will explore various algorithms and models that are required for constructing these new airspaces and enabling optimal traffic routing and overall management.
- Developing automated risk analysis and modelling tools for drone operations
Drone operation will always result in risk to varying degrees and both static and dynamic sources of risk need to be measured, classified and ultimately understood. Static risk includes vulnerable zones such as school yards, car-parks and exposed recreational parks. Dynamic risk includes weather and indeed other drones in flight. This PhD will deal with developing new methodologies and computational models to record, analyse and model risk as a fundamental input to U-Space/UTM system design.
- Sensor fusion for innovative Aerial and Ground based Detect and Avoid (DAA) systems
At the heart of this PhD will be the principle that drones can only fly safely,
undertaking BVLOS operations, if all relevant aspects affecting flight safety are known. One key part of this is emerging optical, radar and RF-Sensor technology for detecting, locating and tracking both fixed and dynamic obstacles at low altitudes. This PhD will focus on how these new emerging technologies can be fused and analysed using the latest Machine Learning techniques to allow drones to fly autonomously over cities, towns and farms, along critical infrastructures and coastlines.
- Adaptable Machine Learning techniques for dynamic aerial scene understanding
Drones are capable of flying for more than an hour, covering tens of kilometres in distance, recording GigaBytes of combined optical and navigation data. Automated classification and measurement of man-made and natural features will become an increasingly important role for data-gathering drones. This PhD will investigate novel Machine learning (ML) tools and methodologies for identifying objects and activities in real-world scenes. These new ML tools will be tested and assessed for a variety of mapping, monitoring, defect inspection and anomaly detection tasks.
Please contact Dr. Lucy Cradden, U-Flyte Project Manager at firstname.lastname@example.org to discuss further.
U-Flyte Doctoral Scholars will receive an annual (tax-free) stipend of €18,000 (paid monthly) and tuition fees over the 4 year PhD duration, will be paid at the EU rate, directly by the project.
Scholars will have a dedicated work-space/I.T. within the NCG’s postgraduate area and join an experienced team operating in an innovative, dynamic environment.