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102 data-science-phd positions in New Zealand

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Gustavo Fonseca Research Masters and PhD postgraduate scholarships in Applied

Home Study Scholarships Search Scholarships Gustavo Fonseca Research Masters and PhD postgraduate scholarships in Applied Conservation Gustavo Fonseca Research Masters and PhD postgraduate

Pūkenga | Lecturer in International Relations

« Back to Jobs Pūkenga | Lecturer in International Relations Location: Kelburn Type: Permanent Post Date: Thu Aug 1 00:50:38 2024 Ref: 1495 Have you got a completed PhD in a relevant field? Do you

Pūkenga - Lecturer in International Relations

of History, Philosophy, Political Science and International Relations . The programme is large, diverse, as well as thriving and supports high-quality research. It teaches students from first-year to PhD level

Pūkenga | Lecturer in Strategic Studies

, full-time Pūkenga - Lecturers in Strategic Studies to join the Political Science & International Relations programme. The anticipated starting date is 24 February 2025 (negotiable). Key responsibilities

Pūkenga - Lecturer (Teaching) in Software Engineering

reflective teaching practices? Do you have a PhD in a related area of computer science and software engineering with a track record of excellent teaching? Are you committed to maintaining high professional and

Pūkenga | Lecturer (Teaching) in Software Engineering

Kairuruku | post doctoral fellow.

you got a proven research and publication track record within evolutionary computation? Do you have a PhD in AI and machine learning and can teach in one or more areas of computer science , including

Postdoctoral Fellow - Microbiology and Immunology

molecular biology, immunology and microbiology. Kā pūkeka me kā wheako/Skills and experience Successful candidates will have: •    A PhD in Immunology, Biochemistry, Pharmaceutical Science , or similar field

Lecturer OR Professional Clinician in Clinical Skills Education

SVS - VetEd - Kauri College of Sciences Palmerston North CS_SVSVEK_521_06/24 SVS - VetEd - Kauri College of Sciences Term length: ongoing Hours of work: full-time To view academic salary scales

Pūkenga Matua | Senior Lecturer in Architecture

technology? Do you hold a Masters degree or PhD in Architecture or a relevant field? Have you got an established track record in research publication or creative work? Mō Te Herenga Waka - About Our University

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Why a New Zealand PhD?

New zealand’s phd package.

International PhD students in New Zealand enjoy the following benefits:

How to apply

Apply now to your preferred university:.

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Jessica Patiño-Pérez | Colombian PhD student

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8 Best universities for Data Science in New Zealand

Updated: February 29, 2024

• Art & Design
• Computer Science
• Engineering
• Environmental Science
• Liberal Arts & Social Sciences
• Mathematics

Below is a list of best universities in New Zealand ranked based on their research performance in Data Science. A graph of 159K citations received by 4.62K academic papers made by 8 universities in New Zealand was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. University of Auckland

For Data Science

2. University of Waikato

3. University of Otago

4. Victoria University of Wellington

5. Massey University

6. Auckland University of Technology

7. University of Canterbury

8. Lincoln University, New Zealand

The best cities to study Data Science in New Zealand based on the number of universities and their ranks are Auckland , Hamilton , Dunedin , and Wellington .

Computer Science subfields in New Zealand

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We have 44 PhD Projects, Programmes & Scholarships in New Zealand

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PhD Projects, Programmes & Scholarships in New Zealand

Fully-funded phd positions in bacterial experimental evolution and computational modelling at the university of auckland, new zealand, phd research project.

PhD Research Projects are advertised opportunities to examine a pre-defined topic or answer a stated research question. Some projects may also provide scope for you to propose your own ideas and approaches.

Funded PhD Project (Students Worldwide)

This project has funding attached, subject to eligibility criteria. Applications for the project are welcome from all suitably qualified candidates, but its funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

Ultrafast Spectroscopy and Organic Light-Emitting Materials

Understanding new zealand values for the future of the food system, development of chemical probes to study phytophthora, competition funded phd project (students worldwide).

This project is in competition for funding with other projects. Usually the project which receives the best applicant will be successful. Unsuccessful projects may still go ahead as self-funded opportunities. Applications for the project are welcome from all suitably qualified candidates, but potential funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

Design and synthesis of chemical tools to interrogate cannabinoid receptors - synthetic, medicinal chemistry

Mechanical measurements using ion pipette aspiration: collaborative experiments, phd scholarship in statistics and data science on model-based clustering for mixed-type data, phd scholarship in applied mathematics on modelling microfluidic phenomena, muka membranes for water treatment, awaiting funding decision/possible external funding.

This supervisor does not yet know if funding is available for this project, or they intend to apply for external funding once a suitable candidate is selected. Applications are welcome - please see project details for further information.

Tissue engineering of cardiovascular implants

Novel broadband terahertz (thz) wave sources using magnetic heusler alloys, "chatgpt" for astronomical light curves, untangling minor planet families, phd project: optical study of protein crystals in space, electromagnetic tracking system for the gut.

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Master of Applied Data Science

UC's Master of Applied Data Science (MADS) This conversion accommodates students from a range of backgrounds who want to build their data science capabilities. Learn more about studying a Master of Applied Data Science through our Te Kaupeka Toi Tangata | Faculty of Science.

Introduction

Data science is a new profession emerging along with the exponential growth in size and availability of 'big data'. A data scientist provides insight into future trends from looking at past and current data. Data science is an essential skillset in a world where everything from education to commerce, communication to transport, involves large-scale data collection and digitalisation.

This conversion Master's is designed to accommodate students from a range of backgrounds (not just those with Mathematics, Statistics, and Computer Science majors), who want to enhance or build their data science capabilities and combine these with the skills and knowledge they bring from their previous studies. So long as you are data-hungry and industry-aware; this degree can add to your employability and career prospects.

The Master of Applied Data Science is offered on campus, by distance, or online through Tuihono UC | UC Online .

What will my study involve? keyboard_arrow_down

What will my study involve.

• One of the few such programmes in Australasia that supports your development from a wider undergraduate study background.
• Potential for work-integrated learning — you may be able to work on an industry data science project during your studies.
• Option to study via distance learning off campus from any location.
• Focus on broader skills required of data scientists such as advanced analytical capability, problem solving, critical thinking, teamwork, and communication skills.
• UC has strengths in the area of data science, including a number of relevant research centres (eg, Toi Hangarau | Geospatial Research Institute , Tangata Hangarau, Hangarau Tangata | HIT Lab NZ , Wireless Research Centre , Digital Humanities ).

Entry requirements keyboard_arrow_down

Entry requirements.

Potential students can come from a variety of undergraduate backgrounds. You will need a B Grade Point Average in 300-level bachelor's degree courses, or have evidence of achievement at postgraduate level.

If English is your additional language, you are also required to meet UC's English language requirements .

For the full entry requirements, see the Regulations for the Master of Applied Data Science or use the admission requirements checker .

How to apply

You can apply online at myUC .

See Admission and enrolment for all information on enrolling at UC.

Degree structure keyboard_arrow_down

How do i plan my degree.

The degree will comprise a minimum of 180 points as follows:

• up to three Foundation Courses
• four courses from advanced data science competencies
• remaining courses from relevant elective options
• DATA601 Applied Data Science Project (45 points).

You can study this qualification full-time in a minimum of 1 year, and part-time in a maximum of 3 years.

The MADS is offered on campus, by distance, or online through Tuihono UC | UC Online .

For full requirements, see the Regulations for the Master of Applied Data Science .

Fees keyboard_arrow_down

2024 tuition fee estimate: $13,316 per 180 points 2025 tuition fee estimate: to be confirmed

International

2024 Special Programme Fee: $52,500 (180 points) 2025 Special Programme Fee: $62,100 (180 points)

Additional costs

Students pay a  Student Services Levy (SSL)  at a rate of $9.17 per point of study in 2024 ($1,100.40 for 120 points). 2025 SSL is yet to be set.

International students must have insurance while studying at UC. Studentsafe insurance is $810 per year of study in 2024.

Domestic tuition fees

International tuition fees

Student Services Levy (SSL)

Insurance for international students

Funding your study

Subjects and courses keyboard_arrow_down

Subjects and courses, foundation courses.

You will be required to enrol in all these foundational courses unless there is evidence of prior learning in the fundamentals of data science (exemptions must be approved by the Programme Director).

The courses are:

• DATA401 Introduction to Data Science
• COSC480 Computer Programming
• MBIS623 Data Management

Advanced Data Science Competencies

All students take the following courses (unless the Programme Director approves a substitution).

• DIGI405 Texts, Discourses and Data: the Humanities and Data Science
• STAT462 Data Mining
• DATA420 Scalable Data Science
• STAT448 Big Data

You should complete the foundation course DATA401, or have a background in statistics, before enrolling in STAT462 and STAT448.

You should also complete the foundation course COSC480, or have a background in Python computer programming, before enrolling in DATA420.

Compulsory course

• DATA601 Applied Data Science Project (45 points)

This compulsory project involves working in a team to solve real-world data science problems.

Elective courses

The remaining courses will be any relevant 400 or 600-level courses in: Biological Sciences , Computer Science , Data Science , Digital Humanities , Economics , Environmental Science , Finance , Geography , Geology , Mathematics , Physics , Psychology , Statistics . Or in any other relevant subject as approved by the Programme Director and the relevant Head of Department.

Some examples of elective courses students have enrolled in recently include:

• COSC421 Advanced Topics in Security
• COSC424 Secure Software
• COSC428 Computer Vision
• DATA415 Computational Social Choice
• DATA416 Contemporary Issues in Data Science
• DATA417 The Trustworthy Data Scientist
• DATA419 Online Communities and Social Networks
• DATA422 Data Wrangling
• DATA423 Data Science in Industry
• DATA424 Information is Beautiful
• DATA425 Foundations of Deep Learning
• DATA430 Medical Data Informatics
• DATA472 Special Topic - Data Engineering
• DATA474 Special Topic - Mathematical Data Science
• BIOL459 Genomics
• GISC404 Spatial Analysis
• GISC412 Spatial Data Science
• GISC422 Foundations of Geographic Information Systems
• HLTH462 Quantitative Health Methods
• INFO620 Information Systems Management
• INFO634 Data Analytics and Business Intelligence
• POLS443 Science, Technology and Environmental Policy
• STAT446 Advanced Generalised Linear and Multivariate Models
• STAT447 Official Statistics
• STAT450 Advanced Statistical Modelling
• STAT455 Data Collection and Sampling Methods
• STAT456 Time Series and Stochastic Processes
• STAT463 Advanced Multivariable Statistical Methods and Applications

Careers keyboard_arrow_down

Career opportunities.

According to industry experts, data scientists know what the technology can offer, what analytics are possible, and can communicate on all those aspects to the wider business. This applies no matter the field or sector, as data and analytics have become so important and integral to organisational decision making. Graduates will be ready to work in a range of industries including: government, corporates, the IT sector, market research and finance, agriculture, and transport.

Aotearoa New Zealand and other countries are currently experiencing a skills shortage in this area, and the need for data-savvy professionals with applied experience is growing.

An Applied Data Science graduate's skills will include:

• advanced knowledge in data science
• the ability to use data to inform workplace solutions
• planning and implementing data-informed projects
• working in multidisciplinary teams
• have an understanding of what programming can offer.

Useful information:

• Read what other UC postgraduate students have gone on to achieve in their studies and careers in our student stories .
• Te Rōpū Rapuara | UC Careers can help you to achieve the career you want, connect with employers, or find a job.
• For research into career destinations by qualification, visit Te Pōkai Tara | Universities New Zealand website .
• Find out more about what can you do with a degree from UC .
• Come along to an upcoming information event for prospective postgraduate students.

Postgraduate Prospectus 2024

Whakatairanga tāura, international prospectus 2024/2025, domestic students.

Student stories

Emil mendoza, 20 july 2023.

"The industry project was a really good learning experience..."

Joo-Hyun Ahn

"The MADS provides high-quality content with solid theories and practical cutting-edge techniques..."

Lakshay Mehra

"Starting my studies via the online-to-on-campus pathway has definitely been the best alternative..."

Nur Syaida Firzana Mohamad Isham

"The entire programme carries out great projects and programmes to help employability..."

Roelant (Rolls) Hofmans

"Data is the currency of business..."

Pratik Mehta

"I was always enthralled how the data-driven world has changed our lives..."

Phuong Tang

"The MADS programme at UC allowed me to gain a wide range of technical competencies..."

Xinmei (Ivy) Zhang

"I think it is a great opportunity for me to broaden my understanding in healthcare via analysing data..."

"The demand for data scientists is extremely high, as the data in our world continues growing exponentially..."

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Master of Data Science MDataSci

Learn how to make decisions using measurable data-driven insights.

Breadcrumbs List.

• Ngā akoranga | Study
• Study options
• Find a study option
• You are currently on: Master of Data Science

Programme overview

The ability to turn data into information, knowledge and innovative products is a skill in high demand within industry. By completing a strong core of Computer Science and Statistics courses, you will gain a unique combination of skills in Data Science and be able to comprehend, process and manage data effectively to extract value from it. Graduates will be critical, reflective practitioners able to pursue professional goals and further postgraduate study.

We also offer the Master of Data Science (MDataSci) as a 240-point taught masters as a March intake only. This is suitable for students who have a background in either Computer Science or Statistics, but not both.  Students who have majored in Data Science, or a combination of computer science and Statistics, should apply for the 180-point taught masters. 

Programme structure

• Entry requirements
• Fees and scholarships

180-point taught masters

• COMPSCI 752 Big Data Management
• COMPSCI 760 Datamining and Machine Learning
• STATS 763 : Advanced Regression Methodology
• STATS 769 Advanced Data Science Practice

At least 15 points from:

• STATS 705 Topics in Official Statistics
• STATS 730 Statistical Inference
• STATS 763 Advanced Regression Methodology
• STATS 784 Statistical Data Mining
• STATS 786 Time Series Forecasting for Data Science
• STATS 787 Data Visualisation

At least 15 points:

• COMPSCI 711 Parallel and Distributed Computing
• COMPSCI 720 Advanced Design and Analysis of Algorithms
• COMPSCI 734 Web, Mobile and Enterprise Computing
• COMPSCI 750 Computational Complexity
• COMPSCI 753 Algorithms for Massive Data

Up to 45 points from:

• COMPSCI 705 Advanced Topics in Human Computer Interaction
• COMPSCI 715 Advanced Computer Graphics
• COMPSCI 732 Software Tools and Techniques
• COMPSCI 761 Advanced Topics in Artificial Intelligence
• COMPSCI 765 Interactive Cognitive Systems
• COMPSCI 767 Intelligent Software Agents
• ENGSCI 711 Advanced Mathematical Modelling
• ENGSCI 755 Decision Making in Engineering
• ENGSCI 760 Algorithms for Optimisation
• ENGSCI 761 Integer and Multi-objective Optimisation
• ENGSCI 762 Scheduling and Optimisation in Decision Making
• ENGSCI 763 Advanced Simulation and Stochastic Optimisation
• ENGSCI 768 Advanced Operations Research and Analytics
• HLTHINFO 723 Health Knowledge Management
• HLTHINFO 728 Principles of Health Informatics
• HLTHINFO 730 Healthcare Decision Support Systems
• INFOSYS 700 Digital Innovation
• INFOSYS 720 Information Systems Research
• INFOSYS 722 Data Mining and Big Data
• INFOSYS 737 Adaptive Enterprise Systems
• INFOSYS 740 System Dynamics and Complex Modelling
• MATHS 715 Graph Theory and Combinatorics
• MATHS 761 Dynamical Systems
• MATHS 765 Mathematical Modelling
• MATHS 766 Inverse Problems
• MATHS 769 Stochastic Differential and Difference Equations
• MATHS 770 Advanced Numerical Analysis
• OPSMGT 752 Research Methods – Modelling
• OPSMGT 757 Project Management
• OPSMGT 760 Advanced Operations Systems
• OPSMGT 766 Fundamentals of Supply Chain Coordination
• SCIENT 701 Accounting and Finance for Scientists
• SCIENT 702 Marketing for Scientific and Technical Personnel
• SCIENT 705 Research Commercialisation
• STATS 701 Advanced SAS Programing
• STATS 710 Probability Theory
• STATS 726 Time Series
• STATS 731 Bayesian Inference
• STATS 770 Introduction to Medical Statistics
• STATS 779 Professional Skills for Statisticians
• STATS 780 Statistical Consulting
• Other 700-level courses approved by the programme director
• DATASCI 792  
• DATASCI 792a 
• DATASCI 792b 
• Dissertation

240-point taught masters

The intake for the 240-point taught masters is in March only.

• COMPSCI 717 Fundamentals of Algorithmics*
• COMPSCI 751 Advanced Topics in Database Systems
• COMPSCI 762 Advanced Machine Learning*
• STATS 707 Computational Introduction to Statistics
• STATS 762 Regression for Data Science
• STATS 765 Statistical Learning for Data Science
• STATS 782 Statistical Computing
• Or other approved 700-level courses offered at this University
• STATS 763 Advanced Regression Methodology
• STATS 730 Statistical Inference  
• STATS 786 Time Series Forecasting for Data Science
• STATS 787 Data Visualisation
• COMPSCI 753 Algorithms for Massive Data
• DIGIHLTH 701 Principles of Digital Health
• DIGIHLTH 702 Health Knowledge Management
• DIGIHLTH 704 Healthcare Decision Support Systems
• MATHS 766 Inverse Problems  
• OPSMGT 752 Research Methods - Modelling  
• OPSMGT 757 Project Management  
• STATS 701 Advanced SAS Programming 
• STATS 710 Probability Theory  
• STATS 726 Time Series  
• STATS 780 Statistical Consulting  
• DATASCI 792 

Postgraduate pathway

Download the Science postgraduate pathway (117KB, PDF)

You'll also need to meet other requirements, including time limits and total points limits. See Postgraduate enrolment .

2024 entry requirements

My highest qualification is from:, programme requirements, minimum programme requirements.

Minimum requirements listed here are the likely grades required and do not guarantee entry. We assess each application individually and applicants may require a higher grade to be offered a place.

Bachelor of Science in Data Science or a Bachelor of Science with a major in Computer Science and a major in Statistics

Bachelor of Science

Calculate your Grade Point Average (GPA)

Further programme requirements

Select your study option:.

You must have completed either:

• A Bachelor of Science in Data Science from this University, with a Grade Point Average of 4.0 or higher in 75 points above Stage II. 
• A Bachelor of Science with a major in Computer Science and a major in Statistics from this University, with a Grade Point Average of 4.0 or higher in 75 points above Stage II.

You must have completed a Bachelor of Science in a similar field with a GPA of 4.0 in 75 points at Stage lll or above. 

An undergraduate science degree

An undergraduate Science degree

No bands less than 6.0

See alternative English language requirements

Calculate your Grade Point Equivalent (GPE)

• You must have completed an undergraduate science degree at a recognised university (or similar institution) in a relevant discipline with a Grade Point Equivalent of 4.0.
• Relevant disciplines include data science, or a mixture of computer science and statistics. A minimum amount of study in a relevant discipline is required - this would be at least a major, field of study, or approximately 30 percent of your degree, including a mix of introductory and advanced courses.

How much does a Master of Data Science cost per year?

Fees are set in advance of each calendar year and will be updated on this website. Fees are inclusive of 15% GST, but do not include the Student Services Fee, course books, travel and health insurance, or living costs. Amounts shown are indicative only. In addition to the tuition fees, there is a Student Services Fee of $8.88 per point, estimated at $1,065.60 for full-time study (120 points). Fees will be confirmed upon completion of enrolment into courses.

*Please note: amounts shown are indicative and estimates only.

See course fees for each faculty

Find out about financial support information

Scholarships and awards.

Find out about the scholarships you may be eligible for.

Student loans and allowances

Are you a New Zealand citizen or resident? You could be eligible for a student loan or allowance.

Cost of living

Get an idea of how much accommodation and general living in Auckland will cost.

Please note: We will consider late applications if places are still available. International students should start the application process as early as possible to allow sufficient time to apply for a visa.

Application closing dates

Where could this programme take you.

With the current demand for continued professional development in this area, this advanced qualification will help you to develop your data science skills to become well-positioned to pursue employment in the data science industry.

Jobs related to this programme

• Business analyst
• Big data solutions architect
• Data mining engineer
• Data scientist
• Digital product designer
• Machine learning engineer

Further study options

• Doctor of Philosophy

Nishita's graduate story

Read what Nishita has to say about studying Data Science at the University of Auckland.

Student career planning service

Once you become a student at the University, you can get help with planning and developing your career from Career Development and Employability Services .

Quick guides to postgraduate Data Science for international students

International guides for Chinese students

International guides for Indian students

Experience the University

Meet the programme director

Learn more about the MDataSci programme from Professor Sebastian Link at the School of Computer Science.

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