PhD Candidate in Machine Learning for Temporal and Spatiotemporal Data

NTNU - Norwegian University of Science and Technology; Trondheim; Presencial; NOK 522.000 - 638.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Free Norwegian language training

Access to high-performance computing

International research environment

Descripción de la vacante

NTNU is offering a four-year PhD position in machine learning for temporal and spatiotemporal data in Trondheim. The project is part of STRIDE, focusing on forecasting and disruption localization on transport networks.

The candidate will develop deep learning methods, publish results, and collaborate across NTNU faculties. The main supervisor is Associate Professor Massimiliano Ruocco; English proficiency and strong ML background are required.

Formación

• Master's degree in computer science, machine learning, statistics, applied mathematics, physics or equivalent (minimum 30 ECTS in major independent project).
• Strong background in deep learning, probability, statistics and linear algebra.
• Excellent programming skills in Python; experience with PyTorch or JAX.
• Experience with transformers and foundation models, graph neural networks, time-series forecasting, anomaly detection.
• Good oral and written English.

Responsabilidades

• Complete the doctoral education until obtaining a doctorate.
• Carry out high-quality research within the described framework.
• Develop, implement and evaluate deep learning methods; release code and benchmarks openly.
• Publish academic work and disseminate science to broad audiences.
• Collaborate within STRIDE and with other PhD candidates and international partners.
• Participate in international conferences / research stays.
• Teaching and other career-promoting activities (one year total).

Educación

Master's degree in computer science or related field

Herramientas

GitHub / GitLab

Descripción del empleo

PhD Candidate in Machine Learning for Temporal and Spatiotemporal Data

NTNU - Norwegian University of Science and Technology

Stillingstittel Phd Candidate in Machine Learning for Temporal and Spatiotemporal Data

NTNU is a broad-based university with atechnical-scientific profile and a focusin professional education. The university is located in three cities with headquarters in Trondheim.

At NTNU, 8,6000 employees and 44,000 students work to create knowledge for a better world.

You will find more information about working at NTNU and the application process here.

The Department of Computer Science (IDI) at NTNU in Trondheim has a vacancy for a PhD Candidate in machine learning (four-year position). The topic of the PhD is machine learning for temporal and spatiotemporal data, that is, time series, including multivariate time series observed on the nodes and edges of a graph, with a focus on forecasting and on detecting disruptions. The position is part of STRIDE, an interdisciplinary NTNU project on the resilience of transport systems (see About the project), and transport networks are the main testbed.

Forecasting models are usually trained on data from normal operating conditions. When a disruption, such as a closed link, a capacity limit or a sudden change in demand, moves a network into a regime that is rare or absent in the training data, their performance degrades, and such events are often too rare to learn from directly. The PhD will develop deep learning methods that forecast reliably under this kind of distribution shift, and that can detect and locate disruptions from the observed data.

Possible research directions include:

• time-series foundation models, including pretraining on synthetic data from simulated dynamical systems, to handle events that are rare in real data
• spatiotemporal graph neural networks that model how disruptions propagate through a network
• anomaly detection and localization of disruptions in time series on graphs

The exact research focus will be defined together with the candidate. We expect the results to be published at leading machine learning conferences and journals.

The main supervisor will be Associate Professor Massimiliano Ruocco, with co-supervisors from the STRIDE team.

Are you motivated to take a step towards a doctorate and open up exciting career opportunities? As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, in and outside academia.

Your immediate leader will be the Head of DART (Data and Artificial Intelligence) group.

About the project

How do we build a society that is resilient to crises, attacks, and unexpected shocks? AMore Resilient Society is a major strategic initiative at NTNU that requires interdisciplinarity and innovative thinking to address complex and socially relevant challenges. A total of 16 PhD candidates will work across faculties and academic communities within the fields of critical societal infrastructure and health preparedness. The aim is to support research that challenges established assumptions and contributes to a safer and more resilient society.

STRIDE (Synergizing Transport Resilience, Infrastructure, and Defense in Extremes) is one of the projects under the More Resilient Society initiative. This is an interdisciplinary research project involving researchers in transport modelling, artificial intelligence, operations research, civil engineering, and science and technology studies. The project studies how transport systems respond to disruptions and how modelling and decision-support methods can strengthen resilience across planning, response, and recovery. The PhD candidate will work closely with three other PhD candidates studying interdependent hazards, data-driven modelling of multimodal transport, and the societal dimensions of resilience and total defense.

Duties of the position

• Complete the doctoral education until obtaining a doctorate
• Carry out research of good quality within the framework described above
• Develop, implement and evaluate deep learning methods, and release code and benchmarks openly
• Academic publications and popular science dissemination
• Take part in STRIDE activities and collaborate with the other three PhD candidates in the project
• Participate in international activities such as conferences and/or research stays at foreign educational institutions
• Teaching and other career-promoting work at the Department of Computer Science (one year in total)
  

Be prepared for changes to your work duties after employment.

• You must have a relevant Master's degree in computer science, machine learning, statistics, applied mathematics, physics or equivalent. Your degree must include a major independent project (minimum 30 ECTS) equivalent to a master’s thesis
• Master students can apply, but the master's degree must be obtained and documented before starting the position and no later than 1 August 2027.
• You must have a strong and relevant academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale . If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker academic background, you may be considered if you can document that you are exceptionally suited for a PhD education, for example through relevant work experience and/or peer-reviewed academic works.
• Good oral and written presentation skills in English
• A strong background in deep learning, and a solid foundation in probability, statistics and linear algebra
• Good programming skills in Python, and experience with PyTorch or JAX
• Experience with one or more of: transformers and foundation models, graph neural networks, time-series forecasting, anomaly detection
• Experience implementing and training deep learning models; provide link to GitHub/GitLab or similar

Personal characteristics

To complete a doctoral degree (PhD), it is important that you are able to:

• Work independently
• Present and discuss your research with other professionals
• Show curiosity and a strong motivation for the subject
• Analyze data, assess different perspectives and draw well-founded conclusions
• Work with researchers from other disciplines and draw on their perspectives

Emphasis will be placed on personal qualities.

We offer

• An exciting job with an important mission in society
• Developing tasks in a strong and international professional environment
• An interdisciplinary team of four PhD candidates, with supervisors from four NTNU faculties
• Access to NTNU's high-performance computing resources, including GPUs
• Open and inclusive working environment with committed colleagues
• Free Norwegian language training at a basic level (A2)

We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.

At NTNU we want to increase the proportion of women in scientific positions. We have a number of measures to promote equality.

Salary and conditions

In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 580 000,-per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted from the salary.

The employment period is four years: three years of doctoral work and one year of career-promoting work.

For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in Computer Science within three months of your employment contract start date, and that you participate in an organized doctoral programme through out the period of employment.

As an employee at NTNU, it is important that you keep yourself up to date with academic and organizational changes and adapt to them.

For the necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis.

The appointment is carried out in accordance with the principles of the State Employees Act , and Export control (legislation that regulates the export of knowledge, technology and services). Candidates who, after assessment of the application and attachments, are considered to bein conflict with the criteria in the latter act, will not be able to be employed.

About the application

The attachments (including a description of your scientific work) must accompany the application as these documents form the basis of the application assessment. The documents must be in Norwegian/a Scandinavian language or English.

Please note: the application will only be assessed on the basis of the information we have received by the application deadline. Therefore, make sure that your application clearly shows how your skills and experience meet the criteria described above. The application and all attachments must be sent electronically via Jobbnorge.no. If you are invited to an interview, you must bring certified copies of certificates and diplomas upon request.

The application must include:

• Transcripts and diplomas for Bachelor's and Master's degrees
• CV
• Copy of Master's thesis. If you have recently submitted your Master's thesis, you can attach a draft of the thesis. Documentation of a completed Master's degree must be presented before taking up the position.
• Research statement describing how you would approach one or more of the research directions described under About the position (maximum 1000 words/2 pages)
• Short letter of motivation (400 words/1 page)
• Publications or other relevant research work, if any, including links to code (for example on GitHub)
• Names and contact information of three relevant referees
  

If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both Bachelor's and Master's education, in addition to other higher education. If your institution uses “diploma supplement” (normal for most European institutions), you must attach this. A description of the documentation required can also be found here . If you already have a statement from Norwegian Directorate for Higher Education and Skills (HK-dir) , please attach this as well.

Joint work will be considered. If it is difficult to identify your contribution to joint work, you must attach a brief description of your participation.

When assessing the best qualified, we emphasize necessary qualifications such as education, experience and personal suitability. Motivation for the position, ambitions, and potential for research will also count when assessing the candidates.

NTNU recognizes a wide range of academic contributions and has committed itself to The San Francisco Declaration on Research Assessment and CoARA (responsible assessment of research and recognition of a greater breadth of academic contributions in accordance with NTNU's social mission).

General information

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you wish to exempt from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation . You will be notified if the exemption is not granted.

If you have any questions about the position, please contact Associate Professor Massimiliano Ruocco, e-mail: [e-mail] .

If you have any questions about the recruitment process, please contact HR at the Department of Computer Science, e-mail: [e-mail] .

The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the tech capital of Norway with a population of 200,000.The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.

The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.

Department of Computer Science

We are the leading academic IT environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied data processing. The Department has groups in both Trondheim and Gjøvik. The Department of Computer Science is one of seven departments in the Faculty of Information Technology and Electrical Engineering .

NTNU - Norwegian University of Science and Technology

NTNU - Norwegian University of Science and Technology

NTNU - Norwegian University of Science and Technology