Senior Data Science Lecturer | Research-led Teaching & Impact in Newcastle upon Tyne

Newcastle University is a great place to work, with excellent benefits. We have a generous holiday package; plus the opportunity to buy more, great pension schemes and a number of health and wellbeing initiatives to support you.

The role:

Applications are invited at Lecturer or Senior Lecturer level in Mathematical or Statistical Data Science, broadly interpreted to include AI. The role will be based within the Statistics and Data Science section in the School of Mathematics, Statistics & Physics (MSP), with a flexible start date to be agreed. You will be expected to carry out excellent research and teaching in an area of Mathematical and/or Statistical Data Science which complements and strengthens existing activities within the School. In addition, there is an opportunity to engage with applied Data Science across a wide range of disciplines within the University, including the School of Computing and the Faculty of Medical Sciences.

You will contribute to the research profile of the Statistics and Data Science Section within MSP by publishing in internationally recognised journals, demonstrating research impact, and securing external research funding. Additionally, you will be a key contributor to the Data Science 2030 (DS2030) faculty project to broaden our institutional offering in data science, alongside the related Artificial Intelligence 2030 project. This will comprise a joined up educational offering at UG and PGT level, and will be sector-leading in providing forward-facing data skills embedded in academic units across all parts of the university. DS2030 will act as a solid platform to build tangible cross-institutional research and business engagement opportunities. DS2030 will be supported by strategic investment and the role holder will be a critical contributor to the success of the project.

Our aim is to employ a rich mix of colleagues with different backgrounds that will help us to:

• contribute new ideas and different perspectives to both teaching and research.
• provide diverse role models and attract a wide range of bright, active, and engaged students.

The University has developed an Academic Job Summary Guidance document which summarises the range of activities that academic staff may be expected to perform.

Key Accountabilities:

Teaching & Learning

• To provide high quality teaching and learning, and student support, across a broad range of Data Science disciplines.
• Mentor and support students throughout their studies in the role of personal tutor.
• Set, and mark, assessment of modules in accordance with University standards and utilise on-line and digitised curricula and education frameworks.
• Contribute to curriculum development in the area of Data Science and beyond in accordance with the requirements of the Statistics and Data Science section.
• Ensure all our students benefit from studying in a research intensive, academic environment.
• Provide education for life, that engages, challenges and supports our students to discover and fulfil their potential both while they are studying with us and once they have graduated.
• Supervise MSc students across a broad range of Data Science disciplines.
• Undertake external professional activities that contribute to the development of applied, methodological or theoretical Data Science.
• Undertake innovative and effective teaching and curriculum design.

Research

• Undertake independent original research in Mathematical and/or Statistical Data Science which demonstrates international standards of excellence in terms of originality, significance and rigour in the subject area.
• Supervise PhD students and postdoctoral researchers across a broad range of Data Science disciplines.
• Publish refereed articles in venues of international standing appropriate to Data Science.
• Collaborate with colleagues in the Statistics and Data Science section.
• Collaborate with colleagues from other disciplines within the university on applied Data Science.
• Seek out external funding opportunities and develop grant-funded research projects.
• Demonstrate impact by developing research-based solutions to real-world problems and engage with external stakeholders to develop the impact of your work.

Other

• Contribute positively to the Vision, Mission and Strategy of MSP as well as the life and work of the School in general.

Administrative Duties

• Carry out administrative duties as assigned by the Head of School and the School Executive Board.
• Demonstrate the ability to advance equity and fairness in higher education through inclusive teaching, research, or professional practice, without compromising the legal protections for academic freedom and freedom of speech within the law.
• Undertake a range of administrative tasks to support your area of teaching, and/or research, and/or engagement for example, recruitment or research team leadership.
• Take responsibility for a defined management or administrative role such as Module Leader, Year Tutor, Degree Programme Director, Research Director, Outreach Coordinator.

Senior Lecturer Responsibilities (Grade H)

• As a senior colleague, make a positive citizenship contribution to the School/Faculty community.
• To provide academic leadership to colleagues and students.
• To have responsibility for the design, development, implementation and administration of successful new courses.
• Attract as well as supervise PGR students in a research-led university.

The Person

Knowledge, Skills and Experience

Essential Criteria – Lecturer (Grade F)

• Ability to deliver high-quality, research-led teaching in Data Science, using appropriate technologies to engage and support students, including supervision of undergraduate and postgraduate projects.
• Evidence or potential to produce high-quality research outputs in Mathematical and/or Statistical Data Science, contributing to the research profile of the Statistics and Data Science section.
• Ability or emerging potential to contribute to research funding bids and collaborative research activity.
• Ability to work collaboratively across disciplines and contribute to team-based activity, with emerging engagement with external stakeholders to support research impact.
• Strong communication, organisational and time management skills, with the ability to contribute positively to School priorities, strategy and academic community.

Additional Criteria – Lecturer (Grade G)

• A developing or sustained international research profile, with a track record of high-quality publications and growing academic recognition.
• Evidence of securing or significantly contributing to externally funded research and delivering impact through stakeholder engagement.
• Experience of designing and delivering high-quality teaching materials and contributing to programme/module development.
• Experience of supervising PGR students and mentoring junior colleagues, alongside consistent supervision of UG/PG research projects.
• Evidence of active contribution to the subject group/School and the ability to take on leadership responsibilities where required.

Additional Criteria – Senior Lecturer (Grade H)

• Experience of leading programme-level design and delivery of teaching, learning and assessment strategies.
• A strong, sustained international research profile with a consistent track record of high-quality outputs and recognition.
• Demonstrated ability to lead teams, initiatives or strategic areas within the School, contributing to its wider academic and operational leadership.

Qualifications

Lecturer Grade F

• A degree (or equivalent) in Data Science, or a closely related discipline such as Mathematics, Statistics, or Machine Learning.
• PhD at or near completion (strictly within three months of submission at time of application) in a relevant subject in Data Science, or a closely related discipline such as Mathematics, Statistics, or Machine Learning.
• A relevant Professional Body Membership as appropriate to the subject area (Desirable).
• HE teaching qualification (or equivalent experience) (Desirable).

Lecturer Grade G

• Completed PhD in Data Science, or a closely related discipline such as Mathematics, Statistics, or Machine Learning.

Senior Lecturer Grade H

• HE teaching qualification (or equivalent experience).

Newcastle University is a global University where everyone is treated with dignity and respect. As a University of Sanctuary, we aim to provide a welcoming place of safety for all, offering opportunities to people fleeing violence and persecution. We are committed to being a fully inclusive university which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all of our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from individuals who can complement our existing teams, we believe that success is built on having teams whose backgrounds and experiences reflect the diversity of our university and student population. At Newcastle University we hold a Gold Athena Swan award in recognition of our good employment practices for the advancement of gender equality. We also hold a Race Equality Charter Bronze award in recognition of our work towards tackling race inequality in higher education. We are a Disability Confident employer and will offer an interview to disabled applicants who meet the essential criteria for the role as part of the offer and interview scheme. In addition, we are a member of the Euraxess initiative supporting researchers in Europe.