Trinity College Dublin

The McCarthy Lab has an exciting opportunity for a prospective Research Technician who is interested in synthetic biology approaches to engineer biofilms to better tackle environmental challenges. You will be joining a highly interdisciplinary project, where we will blend synthetic biology, environmental engineering, and biotechnology to develop disruptive solutions to major environmental challenges. Experience with advanced cloning systems, CRISPR tools, metagenomic mining and the use of different biofilm imaging platforms is highly desirable. There will be a particular focus on developing approaches to harness bacterial community behaviours like biofilm formation to better tackle environmental pollutants such as waste plastics. Our aim is to leverage cutting-edge advancements in synthetic biology and biofilm engineering to develop innovative strategies for bioremediation, with a key focus on scalable solutions that can be readily adopted by the waste and water sectors. This fast-paced project will give the successful candidate the opportunity to develop new skills by working closely with our interdisciplinary team and build their international profile including through research visits to academic collaborators and working with SMEs. The successful candidate will be responsible for accurate and efficient data generation, data management, collation and the reporting of results to the project lead. The post-holder will need to demonstrate excellent attention to detail, organisational, team working and communication skills and have a keen interest in drafting research outputs for peer-review publication. The successful applicant will work closely with other researchers within the McCarthy Lab and with other EBIC partners. There will also be opportunities to explore the commercial  Applicants must have a BSc or MSc in a relevant discipline. Experience and knowledge in the field of biofilm formation is essential. Experience in some or all of the following: advanced cloning systems, CRISPR tools, metagenomic mining and the use of different biofilm imaging platforms is highly desirable. They should be enthusiastic, well motivated and be able to work both independently and collaboratively. This position is available for 32 months. Please include one paper or preprint that illustrates research skills that are relevant to this project.  We are committed to equality, diversity and inclusion and welcome applicants who support our mission of inclusivity. Working at the University of Southampton: Check out the staff benefits and why you should join us at The University of Southampton.

nowRef.: 534889 Work type: Full-time Department: School of Biomedical Sciences (22600) Categories: Teaching Staff Applications are invited for appointment as Senior Lecturer (several posts) in the School of Biomedical Sciences (Ref.: 534889), to commence as soon as possible, on a three-year fixed-term basis, with the possibility of renewal. Applicants should have a Ph.D. degree in Biomedical Sciences, Life Sciences, or other cognate disciplines, with at least 5 to 10 years of relevant teaching experience. They must demonstrate proven leadership in course coordination and substantial teaching experience in anatomy, physiology, biochemistry, for medical, nursing, pharmacy, and biomedical sciences degree programmes. Applicants should be able to demonstrate adoption of innovative approaches in teaching and learning, a record of driving curricular reform, and/or collaboration across disciplines. Evidence of participation and achievement in educational research, including teaching grants and publications, is essential. Good student feedback is an advantage. Applicants should also be inspiring to students, with clear strategies to foster students’ confidence and competence in critical thinking, analytical reasoning, communication skills, and ethical values. The appointee will be involved in the delivery and leadership of teaching at both undergraduate and postgraduate levels, as well as mentoring the junior teaching staff in the School. A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. At current rates, salaries tax does not exceed 15% of gross income. The appointment will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totalling up to 15% of basic salary. Housing benefits will be provided. The University only accepts online applications for the above posts. Applicants should apply online and upload an up-to-date C.V. together with a teaching statement. Review of applications will commence from May 6, 2026 and continue until 31 May 2026, or until the posts are filled, whichever is earlier. Advertised:Apr 23, 2026 (HK Time) Applications close:May 31, 2026 (HK Time)

Role Overview As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have opportunities to tackle real-world, industry-relevant problems, working alongside faculty members and professional officers. The SIT Centre for Intelligent Robotics (CIR) is an applied research centre responsible for developing and maintaining core applied robotics and embodied AI capabilities for real-world deployment. CIR is seeking a Robotics Engineer to implement state-of-the-art learning-based robotic manipulation methods on physical platforms for industry-driven applications, with an emphasis on contact-rich manipulation, robustness, and safe operation. The successful candidate will work closely with physical robots to translate recent advances in learning-based robotics into reliable, deployable systems. Key Responsibilities Implement, adapt, and evaluate state-of-the-art learning-based methods (e.g. imitation learning) for contact-rich robotic manipulation. Integrate hardware and software components into a functional system for real-world deployment. Design and execute field trials (test protocols, data logging, troubleshooting, reliability improvements). Produce technical documentation, reports, and implementation guides to support knowledge transfer and maintainability. Support project procurement activities (e.g., technical specifications, vendor evaluation, quotations) for robotics hardware, sensors, and compute resources. Contribute to publications and technical notes to disseminate research outcomes. To communicate and liaise with any internal and external stakeholders to ensure project deliverables are met. Any other ad-hoc duties assigned by supervisor. Requirements Bachelor’s degree or higher in Robotics, Computer Science, Mechanical Engineering, Control Engineering, or a related field. Experience in imitation learning and reinforcement learning for robotics applications. Hands-on familiarity with robotic manipulators and motion planning. Proficiency in deep learning frameworks such as PyTorch or TensorFlow. Experience with ROS / ROS 2 for real-robot software integration. Proficiency in Python and C++, with good software engineering practices (version control, testing, maintainable code). Familiarity with robotics simulation tools such as Gazebo, Isaac Sim, or MuJoCo. At least 2 years of experience in robotics research or industry projects.