IBM Ph.D. Fellowship If you are currently taking into account Ph.D. courses all around the world then you can take into account the IBM academic global University scholarship program. The IBM organization provides Ph.D. Fellowship for the people who are taking into account various Ph.D. courses related to computer science and this is scholarship program is available since 1951 in order to address the students who have found interest in areas of Technology. You can check out the details related to IBM Ph.D. Fellowship 2023 is given below and we will also share with you all the details of the eligibility criteria and the last date to apply online. We will also share with you all the step-by-step procedures through which you will be able to apply online for this scholarship.
About IBM Ph.D. Fellowship 2023
The IBM Ph.D. Fellowship award program received hundreds of applications from 183 universities in 32 countries and these applications are reviewed by eminent technology from across the organization. The candidates are selected based on their academic excellence and also the innovative and exceptional research proposals that they have submitted in order to get the Ph.D. fellowship award. The organization has been providing fellowships for the last 70 years and it has organized various fellowship programs for students who are doing Ph.D. from around the world. The applicant must follow the eligibility criteria in order to apply for the IBM Ph.D. Fellowship.
Also Read: Citizens of the World Scholarship
Subjects Of IBM Ph.D. Fellowship
The following subjects are included in the Ph.D. scholarship presented by the organization as of 2023:-
- Hybrid Cloud
- Optimization of open standards and open-source code resulting in the enablement and creation of a seamless hybrid cloud platform that can be deployed anywhere. Proposals can include Platform Enablement and Optimization with an open-source component, or use this category for interdisciplinary entries.
- Flexibility and Scalability. Submittals could propose research that leads to the creation of hybrid cloud platforms that enables more flexible, scalable computing, unifying local environments with a virtually limitless pool of computing power and capabilities, making bits, neurons, and qubits available on demand.
- Accelerating adoption. Making hybrid cloud adoption easier and safer by enhancing agility through automation. Submittals could address leveraging AI for code to help automate essential tasks like application modernization, vulnerability detection in code, troubleshooting of IT reliability issues, and research focusing on cutting-edge technologies in antivirus and other protection mechanisms.
- AI Hardware
- Processing efficiency. The next improvements in devices, architectures, and algorithms Nominations could include research that combines these topics and apply them to Deep Neural Networks far beyond the present architectures of GPUs and CMOS Accelerators.
- Digital AI Cores. New accelerators for existing semiconductor technologies that use reduced precision to speed computation and decrease power consumption using reduced precision techniques.
- Analog Cores. Memory-based technology to advance AI at VLSI, analog memory devices and hardware accelerators, mixed-precision in-memory computing, hybrid design for AI Software, and other 8-bit breakthroughs.
- Heterogeneous Integration. AI applications drive the need for a system-level optimization of AI Hardware through Heterogeneous Integration of Accelerators, Memory, and CPU to enable high-speed/high-bandwidth connectivity components. Proposals can bridge these areas.
- Machine Intelligence/Neural Networks. Machine Intelligence differs from machine learning. Solving some of AI’s greatest challenges using associative reasoning to mimic human intelligence. with brain science.
- AI Engineering
- Optimization. Tools for AI creators to reduce the time they spend training, maintaining, and updating their models. New approaches, strategies, and research to explore advanced problems automatically. Best models for ML and data science pipelines, best architectures for deep learning, and best hyperparameters for AI models and algorithms.
- Privacy and Security. IT Infrastructure consumption models, privacy assurance, hybrid cloud strategies, storage infrastructures, privacy and security assurance held in the hardware, and progressive hybrid cloud infrastructure including storage optimization.
- Neuro Symbolic AI
- Deep Learning combines the power of neural networks with symbolic methods to advance AI reasoning effectiveness.
- Neuro-symbolic AI NLP and QA. Submittals that cover applied challenges posited by neural networks, like symbolic AI, Q&A, probabilistic physics inference models, or new neuro-symbolic techniques. New systems for knowledge-based question answering.
- Secure, Trusted AI
- Building evaluating, and monitoring for trust. AI is developing diverse approaches for how to achieve fairness, robustness, explainability, accountability, value alignment, and how to integrate them throughout the entire lifecycle of an AI application.
- Techniques to detect and mitigate bias in datasets and models. Addressing the need for understanding and removing gender stereotypes, as well as citing and/or rating AI services for bias.
- Robustness, and Privacy. Evaluating and defending machine learning models and applications against adversarial threats and/or conforming to required privacy.
- Explainability, Accountability, and/or Transparency. Advancing an AI system to ‘explain itself.’ Exploring the inner workings of an algorithm to provide stakeholders explanations for different purposes and objectives that are tailored to their needs.
- Security
- Designing for security and compliance in niche areas or across the stack: from the hardware, encryption technologies, and the hybrid cloud platform, to the SecDevOps pipeline. Trusted service identity/ identity access management across the stack or address niche areas such as high assurance through Encrypted Container Images. Research covering any and all arrays of software and platforms is encouraged.
- Quantum Computing
- Advanced foundational quantum information science. Exploring and developing new quantum algorithms to reduce error rates and ensure more accurate and reliable results.
- Quantum hardware. Specialized quantum hardware and systems to scale Quantum volume while also increasing qubit count.
- Quantum circuits and software to explore and develop compelling use cases for this powerful form of computing.
Awards Details
The following awards will be provided to the students up in this fellowship program presented by the organization:-
- Awards for universities in the United States are $60,000 in year one; $35,000 in award year two.
- Awards for other countries vary between $6,000 and $25,000 each award year.
Eligibility Criteria
The applicant must follow the following eligibility criteria to apply for the IBM Ph.D. Fellowship:-
- All nominees must nominate a doctoral faculty member; students cannot nominate themselves.
- All nominees must enroll full-time in a Ph.D. program over the two consecutive academic years of the award or forfeit the fellowship.
- All nominees should have three years remaining in their program at the time of nomination so the fellowship can apply to the last two years of study.
- Nominees that are from U.S. embargoed countries are not eligible for the program.
- All nominees that are receiving a comparable fellowship, internship, or support from another company or institution (except for academic scholarships) during the IBM Ph.D. Fellowship funding period are ineligible for this award
- All nominees must stay in the same program for the duration of the award —no transferring of departments or schools.
Selection Procedure
The applicant must follow the following selection procedure to apply for the IBM Ph.D. Fellowship in 2023:-
- Awardees will select based on their potential for research excellence. All awardees will have an IBM mentor for the duration of the award period and are strongly encouraged to intern during the first or second year of their award. All student visas must align with the terms of the internship.
- Nominating faculty must submit thoroughly developed proposals, remain engaged during the vetting and due diligence process, and use the university domain email address for all correspondence.
- Awardees will select based on the degree to which the nominees’ research aligns with IBM focus areas.
- Awardees will be selected based on academic standing, publications, and endorsements from faculty advisors and department heads receiving a comparable fellowship, internship, or support from another company or institution (except in the case of academic scholarships)
- Nominating faculty must submit thoroughly developed proposals, remain engaged during the vetting and due diligence process, and use the university domain email address for all correspondence.
Also Read: Fellowship in India
View Fellowship Result
To check the fellowship result you will have to follow the simple procedure given below:-
- You will first have to visit the official website of the scheme by clicking on the link given here
- The homepage related to the fellowship programs will open on your screen
- You have to now click on the option called Ph.D. Fellowship Awards and the specifications related to the fellowship will open on your screen.
- The details related to the Ph.D. fellowship will open on your screen.
- You have to click on the option called Ph.D. Fellowship Awards Recipients
- The list of year-wise fellowship awardees will open on your screen and you can click on the relevant year to check the number of beneficiaries.