PhD Data Science and Systems Modelling

PhD Entry Requirements

Academic Qualifications: Prospective PhD applicants are expected to hold a taught Masters degree in a relevant subject area. The university typically requires a minimum of 65% as the standard for academic performance in the completed Masters program.

English Language Proficiency:

• IELTS Requirement: An overall IELTS score of 6.5 or 7.0 is required, with no individual band score falling below 6.0.
• TOEFL Requirement: A minimum overall score of 92 on the TOEFL is accepted, with no sub-score in any section falling below 20.
• PTE Requirement: A minimum overall score of 62 with no individual score below 59.

Students must provide:

• Academic marksheets & transcripts
• Letters of recommendation
• A personal statement - SOP
• Passport
• Other supporting documents as required by the university.

Work experience: Some PhD courses may require relevant work experience in the field.

It is important to note that meeting the minimum entry requirements does not guarantee admission, as the university considers factors such as availability of places and competition for the program. Additionally, some courses may have higher entry requirements or additional selection criteria, such as interviews or portfolio submissions.

Abertay University offers several types of scholarships for international Ph.D. students, each with its own criteria and benefits. 

Merit-Based Scholarships: Awards based on academic excellence, research potential, and achievements. Merit-based scholarships aim to attract high-achieving students to contribute to the university's research community.

Research-Specific Scholarships: Some scholarships are dedicated to students undertaking research in specific fields. These may align with the university's strategic research priorities or emerging academic disciplines.

Partnership Scholarships: Collaborative initiatives between Abertay University and external partners may result in specific scholarships. These aim to strengthen ties with organizations, industries, or governments.

Graduates of Abertay University's PhD in Data Science and Systems Modelling program are poised for diverse and influential career paths within the rapidly evolving landscape of data-driven industries. With a unique blend of advanced skills in data science and systems modelling, they are well-equipped to make meaningful contributions across various sectors.

Data Scientist: PhD holders can pursue roles as data scientists, applying their expertise in statistical analysis, machine learning, and data visualization to extract meaningful insights from complex datasets. They work with organizations to harness the power of data for informed decision-making and strategic planning.

Systems Modelling Specialist: Graduates may specialize in systems modelling, working as specialists who design and develop models to represent complex systems. They contribute to the understanding and optimization of intricate processes within industries such as logistics, finance, and healthcare.

Predictive Modelling Analyst: With a focus on predictive modelling, graduates can become analysts who develop models to forecast trends, patterns, and future outcomes. They work in sectors like finance, marketing, and healthcare, providing organizations with valuable insights for proactive decision-making.

Data Engineer: PhD holders can pursue careers as data engineers, responsible for designing and implementing robust data architectures, databases, and infrastructure. They play a vital role in ensuring data reliability, accessibility, and scalability within organizations.

Machine Learning Engineer: Those with a focus on machine learning can embark on careers as machine learning engineers, contributing to the development of intelligent systems and algorithms. They work on projects ranging from natural language processing to computer vision, pushing the boundaries of AI applications.

Business Intelligence (BI) Consultant: Graduates can become BI consultants, helping organizations leverage data for strategic business decisions. They design and implement BI solutions, create dashboards, and provide actionable insights to support organizational goals.

Research Scientist: PhD holders may choose to pursue research scientist positions, contributing to academia or research institutions. They engage in cutting-edge research projects, advance the understanding of data science methodologies, and publish findings in peer-reviewed journals.

Data Analytics Manager: With experience and leadership skills, graduates can take on managerial roles as data analytics managers. They oversee teams of data analysts, ensure the successful execution of data projects, and align data strategies with organizational objectives.

Healthcare Data Analyst: Those interested in healthcare applications can work as data analysts in the healthcare sector. They analyze patient data, contribute to medical research, and support healthcare organizations in improving patient outcomes through data-driven insights.

Financial Modelling Specialist: Graduates may specialize in financial modelling, working in the finance sector to develop models for risk assessment, investment analysis, and financial forecasting. They contribute to informed financial decision-making within banking, investment, and insurance industries.

Academic and Research Positions: Many graduates choose to contribute to academia, becoming professors, researchers, or lecturers in universities and research institutions. They advance the academic understanding of data science and systems modelling, mentor the next generation of professionals, and lead research projects.

Continuous Professional Development: Remaining committed to continuous learning, graduates can attend conferences, workshops, and industry events to stay updated on emerging trends and technologies in data science. They can also engage in networking opportunities, contributing to thought leadership in the ever-evolving field of data science.