At a Glance
- Tasks: Teach and mentor students in Data Science while conducting impactful research.
- Company: Join Newcastle University, a diverse and inclusive global institution.
- Benefits: Enjoy generous holidays, health benefits, and professional development opportunities.
- Other info: Be part of a supportive community that values diversity and equity.
- Why this job: Shape the future of Data Science and inspire the next generation of innovators.
- Qualifications: PhD in Data Science or related field; teaching experience preferred.
The predicted salary is between 40000 - 55000 € per year.
Newcastle University is a great place to work, with excellent benefits. We have a generous holiday package, 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.
Key Accountabilities
- Teaching & Learning
- Provide high quality teaching and learning, and student support, across a broad range of Data Science disciplines.
- Mentor and support students throughout their studies as personal tutor.
- Set, and mark, assessment of modules in accordance with university standards and utilise online 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 students benefit from studying in a research‑intensive, academic environment.
- Provide education for life, engaging, challenging and supporting students to discover and fulfil their potential during their studies and after graduation.
- 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 demonstrating 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 engaging 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.
- 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.
- As a senior colleague, make a positive citizenship contribution to the School/Faculty community.
- Provide academic leadership to colleagues and students.
- 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.
- 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 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. As a Disability Confident employer we 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.
Lecturer / Snr Lecturer Mathematical employer: Newcastle University
Newcastle University is an exceptional employer, offering a vibrant work culture that prioritises employee wellbeing and professional growth. With generous holiday packages, comprehensive pension schemes, and a commitment to inclusivity, the university fosters an environment where staff can thrive both personally and professionally while contributing to cutting-edge research in Mathematical and Statistical Data Science.
StudySmarter Expert Advice🤫
We think this is how you could land Lecturer / Snr Lecturer Mathematical
✨Tip Number 1
Network like a pro! Reach out to your connections in academia and industry. Attend conferences, workshops, or even local meet-ups related to Data Science. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your teaching skills! If you get the chance, offer to give a guest lecture or workshop at a local university. This not only showcases your expertise but also helps you build relationships with faculty members who could influence hiring decisions.
✨Tip Number 3
Be proactive about research collaborations! Reach out to colleagues in your field and propose joint projects. This can enhance your CV and demonstrate your ability to work across disciplines, which is a big plus for roles like the one at Newcastle University.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our community. Don’t forget to tailor your application to highlight how your experience aligns with the role’s key accountabilities.
We think you need these skills to ace Lecturer / Snr Lecturer Mathematical
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your application to highlight how your skills and experiences align with the role. We want to see how you can contribute to our teaching and research in Data Science, so don’t hold back on showcasing your relevant achievements!
Show Off Your Passion:Let your enthusiasm for teaching and research shine through! We love candidates who are genuinely excited about engaging with students and contributing to the academic community. Share your vision for how you can inspire the next generation of Data Scientists.
Be Clear and Concise:Keep your application clear and to the point. Use straightforward language and avoid jargon where possible. We appreciate well-structured applications that make it easy for us to see your qualifications and potential contributions.
Apply Through Our Website:Don’t forget to submit your application through our official website! It’s the best way to ensure your application gets the attention it deserves. Plus, you’ll find all the details you need to make your application stand out.
How to prepare for a job interview at Newcastle University
✨Know Your Stuff
Make sure you brush up on the latest trends and developments in Mathematical and Statistical Data Science. Be ready to discuss your research interests and how they align with the university's goals. This shows you're not just knowledgeable but also genuinely interested in contributing to their academic community.
✨Engage with Your Audience
During the interview, remember that it's a two-way street. Prepare thoughtful questions about the teaching methods and curriculum development at the university. This demonstrates your commitment to high-quality education and your eagerness to engage with students and colleagues alike.
✨Showcase Your Teaching Style
Be prepared to share examples of your teaching philosophy and how you've successfully engaged students in the past. If you have any innovative teaching materials or methods, bring them along to showcase your approach. This will help the interviewers visualise how you can contribute to their teaching environment.
✨Highlight Collaboration Skills
Collaboration is key in academia, so be ready to discuss your experience working with others on research projects or curriculum design. Share specific examples of how you've contributed to team-based activities and how you plan to foster collaboration within the Statistics and Data Science section.