Ph.D. in Machine Learning & Artificial Intelligence
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The PhD in Machine Learning & AI at Dunster Business School, Switzerland is designed for professionals and researchers who want to master cutting-edge AI and ML technologies. The program provides deep expertise in algorithm development, data-driven decision-making, and intelligent systems, addressing the growing global demand for AI-skilled leaders. It is essential for anyone aiming to secure future-ready, high-impact roles in research, technology innovation, and strategic decision-making across industries worldwide.
Program Highlight
About Programs
The PhD in Machine Learning & AI at Dunster Business School, Switzerland provides advanced knowledge and research skills in artificial intelligence, deep learning, neural networks, and data-driven problem solving. The program equips students to tackle complex real-world challenges, innovate in emerging technologies, and contribute to cutting-edge research. For a career, it opens doors to high-level roles in AI research, R&D, technology leadership, and strategic analytics, both in India and internationally, making professionals highly competitive and future-ready in the rapidly evolving AI-driven market.
Ph.D. in Machine Learning & Artificial Intelligence (24 -36 Months)
Intake: 2026 - 2027
Typical Program Structure
A PhD in Machine Learning & Artificial Intelligence equips professionals with deep expertise in AI and machine learning, making them valuable for complex, high-level roles that are less likely to be automated. It builds strong research and problem-solving skills, enabling adaptability as the AI-driven job market continues to evolve.
- Duration: 24-36 Months (Online)
- Total Credits: Varies by institution (e.g., 60-120 credits).
- Structure: Heavily focused on taught coursework and often culminates in a capstone project or dissertation completed over the summer.
Core Curriculum Topics
Advanced Machine Learning
- supervised, unsupervised, and reinforcement learning algorithms
Deep Learning & Neural Networks
- CNNs, RNNs, transformers, and AI model optimization.
Artificial Intelligence Foundations
- search algorithms, reasoning, knowledge representation.
Big Data Analytics & Computational Methods
- handling large datasets, distributed computing, and AI pipelines.
Research Methodology & Scientific Computing
- designing experiments, statistical modeling, and high-performance computing for AI research.
Curriculum Overview
A PhD in Artificial Intelligence and Machine Learning (Dunster-style, industry-oriented) typically combines strong research foundations with modern, applied AI topics. The program begins with doctoral research methods, academic writing, and ethics in AI, and then moves into advanced machine learning systems such as deep learning, transformers, reinforcement learning, and AutoML. It further covers cutting-edge areas like generative AI and large language models, multimodal systems, and synthetic data. A strong emphasis is placed on AI engineering and MLOps, including deployment, scalability, and real-time systems, along with data intelligence and decision science using big data architectures.
Curriculum Breakdown Summary
A PhD in Artificial Intelligence and Machine Learning (Dunster-style, industry-oriented) typically combines strong research foundations with modern, applied AI topics. The program begins with doctoral research methods, academic writing, and ethics in AI, and then moves into advanced machine learning systems such as deep learning, transformers, reinforcement learning, and AutoML. It further covers cutting-edge areas like generative AI and large language models, multimodal systems, and synthetic data. A strong emphasis is placed on AI engineering and MLOps, including deployment, scalability, and real-time systems, along with data intelligence and decision science using big data architectures.
| Regular Students | Required Credits |
|---|---|
| Advanced Machine Learning & Deep Learning | 30 Credits |
| Generative AI & Intelligent Systems | 30 Credits |
| AI Applications & Strategic Integration | 15 Credits |
| Responsible, Ethical & Governed AI | 15 Credits |
| Research Methodology & Scientific Computing | 30 Credits |
Our Alumni
Dr. Ronald M. Gharib
Doctorate in Business Administration, Strategic Management
Dr. Shiv Kumar Dadar
Doctorate Holder in AI & Business Strategy domain
Dr. Jeegnesh Trivedi
Honorary Doctorate, Education
Dr. Prannay G Sharma
Honorary Doctorate, Sales and Leadership
Dr. Hariraj Chouhan
Honorary Doctorate in Management
Dr. Laksh Narayanan G.
Doctor of Philosophy - PhD, Human Resources Management and Services
Dr. Gautam Kumar
Honorary Doctorate In Business Administration
Dr Ninad Waaykole
Doctorate , Automotive AI EngineeringProgram Cost
A PhD in Artificial Intelligence and Machine Learning from Dunster Business School can be viewed as a strategic investment in long-term career positioning rather than a short-term academic return. While the cost of the program is relatively lower and more flexible compared to traditional university doctorates, the ROI comes from enhanced professional credibility, global positioning, and access to high-growth AI-driven opportunities. As industries across the world rapidly integrate AI into decision-making, operations, and innovation, professionals with doctoral-level expertise in AI and ML are increasingly valued in consulting, leadership, and advisory roles. The program’s focus on applied research, emerging technologies like generative AI, and real-world problem solving ensures that learners stay aligned with future market demands. In that sense, it acts as a future-proof investment, enabling professionals to remain relevant, build authority in a fast-evolving domain, and capitalize on the expanding global AI economy.
| Program | International Student Fee | Indian Students Fee | Scholarship | Zero Cost EMI's | Payment Mode |
|---|---|---|---|---|---|
| Ph.D. in Healthcare Management | $ 22,500/- | INR 5,99,999/- | Upto 40% | 12 Months | NEFT / Payment Gateway |
Apply Now
Choosing a PhD in ML & AI is a strategic decision for students who want to build a long-term, future-proof career in an AI-driven world. As industries rapidly shift toward automation and data-led decision-making, professionals with deep expertise in machine learning, analytics, and research are becoming increasingly valuable and harder to replace. While the journey requires time and dedication, the ROI is strong—offering access to high-paying global roles, leadership opportunities, and the ability to work on cutting-edge innovations. In the long run, it’s not just a degree, but an investment in career stability, global mobility, and staying relevant in a technology-driven future.
Requirements and Deadlines
For the PhD (Machine Learning & Artificial Intelligence) program at Dunster Business School Switzerland, you need a master’s degree (or equivalent) in a related field and a strong academic/research background, along with a clear research plan and proficiency in English, as admissions are designed for serious researchers and professionals seeking advanced expertise. The program is research‑intensive and includes guided mentorship, original thesis work, and engagement with a global academic community, preparing you for leadership, research, or academic roles worldwide. Since admissions for the 2025–2026 cycle are still open but closing soon, you should prepare and submit your application, statement of purpose, transcripts, and any required references without delay, as delayed submission may mean waiting for the next intake.