PhD Candidate: Network Science for Green AI

PhD Candidate: Network Science for Green AI

Published Deadline Location
28 May 30 Jun Nijmegen

Job description

Would you like to play a part in pioneering data science methods that promote sustainability and reliability in AI? Are you eager to delve into the application of network science for unlocking the secrets of the AI "black box"? Then come and join us as a PhD candidate to explore and innovate energy-efficient methods for machine learning training.

Artificial Neural Networks (ANNs) are driving new applications in AI, data science and intelligent systems. Yet, their training demands significant computational power, leading to a need for energy-efficient techniques that work well on lightweight devices. Random sparse ANNs have shown promise in addressing this challenge. However, the full understanding of these models remains unclear. Developing green AI techniques poses significant challenges, including addressing energy consumption, optimising efficiency, and ensuring scalability to meet the demands of complex tasks and large-scale deployments. As a PhD candidate, you will leverage tools from network science to tackle these challenges and gain insights into the training dynamics of ANNs.

As a PhD candidate at Radboud University, you will spearhead the frontier of machine learning innovation. Dive into crafting groundbreaking miniaturised architectures for training sparse ANNs, while delving deep into their evolution during training using cutting-edge tools from the network science domain.

You will spend roughly 10 percent of your time (0.1 FTE) helping with the teaching activities in our department. For example, you may be asked to tutor practical assignments, grade coursework, give presentations during classes, or supervise student projects.

You will be supervised by Dr Lucia Cavallaro and Prof. Tom Heskes, researchers with strong expertise in both network science and artificial intelligence.

The Institute for Computing and Information Sciences (iCIS) values a diverse workforce. Female candidates are therefore particularly encouraged to apply.

Specifications

Radboud University

Requirements

  • You hold an MSc degree in computer science, data science, machine learning, mathematics, or a related field.
  • You are proficient in programming languages used in scientific computing, such as Python, and you have a strong interest in further developing your programming skills.
  • You might be a data scientist interested in exploring networks and graphs to solve real-world problems, a network scientist looking to specialise in data science and machine learning, or a combination of both. If you are eager to deepen your knowledge in any of these areas where you may have less experience, we encourage you to join us.
  • You are fluent in verbal and written English.
  • You enjoy working in a multidisciplinary environment and would like to further develop your good communication, presentation and writing skills.

Conditions of employment

Fixed-term contract: 1,5 years, after which your performance will be evaluated. If the evaluation is positive, your contract will be extended by 2.5 years (4-year contract) or 3.5 years (5-year contract).

  • We will give you a temporary employment contract (0.8 FTE 5- year contract - 1.0 FTE 4- year contract) of 1,5 years, after which your performance will be evaluated. If the evaluation is positive, your contract will be extended by 2.5 years (4-year contract) or 3.5 years (5-year contract).
  • You will receive a starting salary of €2,770 gross per month based on a 38-hour working week, which will increase to €3,539 from the fourth year onwards (salary scale P).
  • You will receive an 8% holiday allowance and an 8,3% end-of-year bonus.
  • You will be able to use our Dual Career and Family Support Service. The Dual Career Programme assists your partner via support, tools, and resources to improve their chances of independently finding employment in the Netherlands. Our Family Support Service helps you and your partner feel welcome and at home by providing customised assistance in navigating local facilities, schools, and amenities. Also take a look at our support for international staff page to discover all our services for international employees.
  • You will receive extra days off. With full-time employment, you can choose between 30 or 41 days of annual leave instead of the statutory 20.

Work and science require good employment practices. This is reflected in Radboud University's primary and secondary employment conditions. You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.

Department

The Data Science group is part of the Institute for Computing and Information Sciences

(iCIS) at Radboud University. We develop theory and methods for machine learning and apply them in various fields. During recent evaluations, iCIS has been consistently ranked as the No. 1 Computing Science department in the Netherlands. Evaluation committees praise our flat and open organisational structure and our ability to attract external funding.

Our group is very friendly and welcoming; the atmosphere you will experience is relaxed and yet productive. You will be part of our gender mixed group with diverse backgrounds and cultures.

Please see Lucia Cavallaro’s Google Scholar profile for examples of the kind of research we are involved in and the techniques we use.

Additional information

Address your letter of application to Dr. Lucia Cavallaro. In the application form, you will find which documents you need to include with your application.

The first interviews will take place between 8 and 12 July. You will preferably start your employment on 1 September 2024.

We can imagine you're curious about our application procedure. It describes what you can expect during the application procedure and how we handle your personal data and internal and external candidates. If you wish to apply for a non-scientific position with a non-EU nationality, please take notice of the following information.

Specifications

  • PhD
  • Natural sciences
  • 30.4—38 hours per week
  • €2770—€3539 per month
  • University graduate
  • 62.071.24

Employer

Location

Houtlaan 4, 6525XZ, Nijmegen

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Application procedure

Application procedure

Make sure to apply no later than 30 Jun 2024 1:59 (Europe/Amsterdam).