Rajamangala University of Technology Suvarnabhumi

About the University of Bristol: The University of Bristol’s Mumbai campus is an innovative extension of its prestigious UK counterpart, established to promote academic excellence, global collaboration, and impactful industry engagement in one of the world’s most dynamic financial hubs. The campus offers a truly international and cross-cultural academic environment, combining the University’s rigorous academic traditions with the fast-evolving Indian and South Asian business landscape. As part of a growing global network, the Mumbai campus serves as a hub for interdisciplinary learning, applied research, and thought leadership. Faculty members enjoy access to global partnerships, collaborative research opportunities, and the ability to contribute to high-impact academic programmes that prepare students to meet the challenges of an interconnected world. Role Overview We are seeking a highly motivated and accomplishedAssociate Professor in Data Science / Statistics to join our growing academic team at the University’s Mumbai Enterprise Campus (MEC), a flagship transnational education initiative of the University of Bristol set to open its doors in 2026, coinciding with the University’s 150th anniversary. The role will lead on curriculum and research development, mentor junior faculty, and strengthen the University’s academic reputation through teaching, innovation, high-impact research and external engagement. The role will report to the Mumbai Enterprise Campus Associate Dean and have dotted lines reporting to and collaborating with the Head of School of Mathematics in the Faculty of Science and Engineering (S&E), and other relevant University senior leaders. This senior-level position is ideal for candidates with a strong academic profile, proven research excellence, and leadership capabilities within higher education. Key Responsibilities Leadership, Culture, and Engagement Provide distinguished academic leadership and operational capacity in both teaching and research within mathematical statistics or data science fostering an environment of scholarly excellence. Represent the university at national and international academic and professional forums, enhancing its visibility and reputation. Establish and nurture strategic partnerships with industry, academic institutions, and government agencies to support research initiatives and enrich the learning environment. Contribute substantively to departmental governance, administration, and operational delivery in close collaboration with senior leadership. Develop, coordinate, and deliver advanced undergraduate and postgraduate courses in areas ranging from mathematical statistics and machine learning to coding and algorithmics. Mentor junior and early-career faculty members, actively participating in their professional development and performance evaluation processes. Work collaboratively with Professional Services partners to deliver delegated administrative and governance duties. Teaching Play a pivotal role in curriculum development and contextualisation, programme accreditation, programme enhancement and the maintenance of quality assurance standards within the university. Create a nurturing environment for excellence across the whole education offer. Promote innovative teaching strategies that improve student experience, transferable skills creation and employability prospects. Research Maintain a sustained record of high-quality outputs in excellent, peer-reviewed academic publications or in other recognised  discipline specific channels, actively contributing to the international discourse in mathematical statistics and data science. Initiate, lead, and secure funding for research projects with significant potential to contribute to scholarly knowledge and societal advancement. Provide support for other academic disciplines and interdisciplinary opportunities within the MEC. Ensure research strengths are matched and leveraged to develop teaching excellence and integrated in MEC programme offerings. Where applicable, supervise and mentor doctoral, postgraduate, and undergraduate research projects, ensuring the highest standards of academic rigor and integrity. Essential Criteria A completed PhD in mathematical statistics and data science. Significant academic experience, including substantial post-PhD teaching and research achievements Proven academic leadership experience in teaching (e.g., programme coordination, research leadership, or departmental roles). Demonstrated excellence in teaching, curriculum design, and academic mentorship. Strong publication record in highly ranked peer-reviewed international publications, or in recognised equivalent discipline-specific channels, and ability to contribute to the school’s strategic research ambition to address global/societal challenges of our time. Evidence of excellent organisational and administrative skills. Excellent interpersonal, communication, and collaborative leadership skills. Demonstrates a proactive approach to professional development. Strong programming expertise. Expertise is machine learning and data science. Desirable Criteria At least 10-12 years of academic experience post-PhD Track record of securing or leading externally funded research projects. Willingness and strong evidence to seek collaborations/engage with public, private and not-for-profit/charitable sectors. Experience supervising doctoral students A teaching qualification recognised by the UK Higher Education Academy or equivalent. For any concerns regarding your application, kindly reach out to us at careers@daskalos.com

About the University of Bristol: The University of Bristol’s Mumbai campus is an innovative extension of its prestigious UK counterpart, established to promote academic excellence, global collaboration, and impactful industry engagement in one of the world’s most dynamic financial hubs. The campus offers a truly international and cross-cultural academic environment, combining the University’s rigorous academic traditions with the fast-evolving Indian and South Asian business landscape. As part of a growing global network, the Mumbai campus serves as a hub for interdisciplinary learning, applied research, and thought leadership. Faculty members enjoy access to global partnerships, collaborative research opportunities, and the ability to contribute to high-impact academic programmes that prepare students to meet the challenges of an interconnected world. Main Job Purpose The candidate will contribute to the delivery of high-quality teaching, assessment, and dissertation supervision in Data Science / Statistics, at the UG level. The main area of interest is Data Science / Statistics. Main Responsibilities Teaching Responsibilities Teaching at Undergraduate and Postgraduate including assisting with lectures, tutoring, seminars. and computer lab sessions. Acting as a personal tutor to undergraduate and postgraduate students. Supervising UG/MSc dissertations in the relevant area. Marking exams and coursework papers for graduate and undergraduate students; with Curriculum development/enhancement in line with the school ambition/strategy. Actively contributing to the function of the school by attending meetings and seminars and undertaking administrative duties assigned by the Head of School. Proactive approach to professional development and scholarship. Administration Responsibilities If needed, fulfilling the role of unit/course director or aiding unit/course director in the administration, development, and teaching of the relevant unit. Responsibilities are likely to include administering graduate and undergraduate degree programmes (Financial Technology or similar, including new programme development, promotion and admissions; organising and monitoring delivery of units; overseeing the welfare of students; liaising with external examiners; and/or reviewing and revising programmes in accordance with school and faculty policy. Making a wider contribution to the success of the University from their participation in faculty and University wide governance and development activities. Other leadership and administrative duties as assigned by the Head of Group. Relationships Line manager: Assistant Professor Line manager to (where appropriate): Not applicable. Internal Contacts: School and faculty staff School undergraduate and postgraduate students Staff and students in the wider university. External Contacts: Research collaborators. Dissertation supervisors. External Partner Organisations. PERSON SPECIFICATION Relevant Experience, Skills and Knowledge Evidence of experience and ability to teach effectively at undergraduate and master's levels in a relevant discipline, including in small-group and/ or lecture settings. Evidence of a proactive approach to teaching and student engagement. Evidence of taking initiative to improve students’ learning. Evidence of excellent organisational and administrative skills. Experience of effectively supervising undergraduate and masters’ projects and dissertations. Evidence of responsibility for planning your own professional development. Evidence of ability to contribute effectively to the administration and management of the department, school and faculty. Evidence of leadership responsibility in teaching and learning (e.g. leading new courses/programmes and personal tutor role). Relevant Qualifications A Doctorate (e.g. PhD or expected to be completed by the start of appointment) in an appropriate discipline, which fits with teaching specialism/s. HE teaching qualification. Links with accreditation bodies. Digital/Blended learning experience Communication and Interpersonal Skills Excellent interpersonal skills for collaborative working. The ability to communicate effectively both orally and in writing to different audiences. Flexibility and ability to adapt to changing circumstances. Additional Criteria Use of digital learning and collaboration tools and software, e.g. Key languages are R, C++ and Python. For any queries related to your application, email at careers@daskalos.com

Department: Central European Institute of Technology Deadline: 31 May 2026 Start date: 2027-2028 Job type: full-time Job field: Science and research INDUSTRIAL CHAIR / RESEARCH GROUP LEADER IN LIFE SCIENCES  Central European Institute of Technology of the Masaryk University (CEITEC MU), Brno, Czech Republic CEITEC MU is the Czech Republic´s flagship institution, renowned for its biomedical research and cutting-edge core facilities. CEITEC MU aims to strengthen its collaboration with industry and the application sphere, and is therefore seeking outstanding candidates in applied research. About this position We invite outstanding researchers currently based outside the Czech Republic to establish a research group at CEITEC MU with the support of the TAČR Industrial Chair call. If your expertise aligns with CEITEC MU’s strategic priorities and research areas, and you bring a strong scientific vision combined with a proven track record of collaboration with industry, we would be delighted to hear from you. The establishment of the research group at CEITEC MU is contingent upon obtaining support from the TAČR Industrial Chair programme. If the proposal is awarded, we will offer you a Research Group Leader position at CEITEC MU. In this role, you will: Build and lead a team of researchers working at the intersection of AI and biomedical sciences. Develop novel AI methodologies enabling next-generation analysis of complex biological systems. Collaborate with core facilities and international partners to co-develop AI-enabled research workflow and instrumentation. Work closely with leading industry partners in the region to translate AI-driven research into real-world applications. Actively pursue and secure external funding to support the development of the group and its research activities We are looking for candidates who meet the following mandatory criteria: At least 5 years of ongoing research experience outside the Czech Republic at the time of application. No current or previous affiliation with Masaryk University. In addition, candidates should be able to demonstrate: A track record in AI research with applications in life sciences. Proven experience in applied research and collaboration with industry. The ability to identify impactful research challenges at the interface of AI and life sciences. The capacity to conduct independent research using advanced computational and data-driven methodologies. Excellent interpersonal skills and leadership abilities, including the capacity to supervise early-stage researchers and mentor others. The ability to communicate effectively with the scientific community, industry partners, and the broader public about AI applications in life sciences and their societal impact. What else do you need to know: Application Deadline: 31.5.2026 Assessment of Applications: on an ongoing basis Expected Start: 2027-2028 Applications including a CV, list of publications, description of skills and experience related to the advertised position, 2-page outlook of future research interests, and contacts for at least two references, should be sent via e-application - you can find the link above and below the text. For informal inquiries about the position and CEITEC MU, or in the case of difficulties with the e-application, please contact: hr@ceitec.muni.cz For more information about the recruitment process, refer to CEITEC Recruitment Policy. In justified cases, the job announcer can extend, interrupt, or cancel the selection procedure.