Doctoral student in Machine Learning for Integrated Resources Modelling Full-time NEW

Doctoral Student In Machine Learning For Integrated Resources Modelling

KTH Royal Institute of Technology, School of Industrial Engineering and Management

Project description

Third-cycle subject: Energy and Environmental Systems

The division of Energy Systems (dES) within the Department of Energy Technology at KTH has been driving the advancement of energy systems and integrated resource assessment methodologies for supporting integrated resource planning in developed and developing countries, through funding from UK Aid, UN and European Union. The division is now hiring a PhD student who shall work on a step change in the methodologies by using Machine Learning, whose benefits will cut across these funding streams. The student's work will focus on using ML to generate workflows that enable the exploration of uncertainties and of wide scenario spaces in large and granular bottom-up integrated resource models. This shall support fit-for-context modelling in chosen developed and developing contexts that the division works in. Travels and engagement with government and stakeholders in the selected contexts and participation in capacity development activities will be part of the regular tasks of the student.

Supervision: Francesco Gardumi is proposed to supervise the doctoral student. Decisions are made on admission

Admission requirements

To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:

• passed a second cycle degree (for example a master's degree), or
• completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
• acquired, in some other way within or outside the country, substantially equivalent knowledge

In addition to the above, there is also a mandatory requirement for English equivalent to English B/6.

Selection

In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:

• independently pursue his or her work
• collaborate with others,
• have a professional approach and
• analyze and work with complex issues.

You should also have good knowledge of energy technology and integrated resource systems, as well as modeling within the field, including data processing and Machine Learning techniques.

You shall be able to engage and collaborate with external partners and stakeholders in Sweden and abroad.

After the qualification requirements, great emphasis will be placed on personal skills.

Target degree: Doctoral degree

Information regarding admission and employment

Only those admitted to postgraduate education may be employed as a doctoral student. The total length of employment may not be longer than what corresponds to full-time doctoral education in four years' time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment may be renewed for a maximum of two years at a time. In the case of studies that are to be completed with a licentiate degree, the total period of employment may not be longer than what corresponds to full-time doctoral education for two years.

As a doctoral student, you are entitled to a workplace with many employee benefits and monthly salary according to KTH's Doctoral student salary agreement . Read more about Doctoral studies (PhD) | KTH | Sweden.