ORGANISATION/COMPANYDelft University of Technology (TU Delft)
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE31/08/2020 01:59 - Europe/Brussels
LOCATIONNetherlands › Delft
TYPE OF CONTRACTTemporary
HOURS PER WEEK38.0
The Delft Tensor AI Lab (DeTAIL) focuses on both the development and application of novel low-rank AI tensor methods. The main focus of applications is primarily in the field of biomedical signal processing. DeTAIL currently has 2 PhD projects:
Large-scale tensor-based kernel methods: Kernel methods have become well-established nonparametric machine learning methods for both unsupervised and supervised problems. The key ingredient in kernel methods is the kernel matrix which contains the evaluations of a chosen kernel function in the measured data. Inversion of this kernel matrix quickly becomes a problem for large-scale data. Your research focus will be on solving this problem through the development of novel kernel methods based on low-rank tensor approximations.
Learning nonlinear dynamics from uncertain data with tensors: Modelling dynamical processes is a crucial component in developing knowledge and is usually the first step in applications. For most real-life processes it is too difficult or even impossible to derive a model from first principles. In these cases, a model has to be learned from measured data. Two major challenges in learning dynamics from data are nonlinearity and noise. Models that describe nonlinear dynamics consist of considerably large amounts of parameters and therefore large amounts of data are required for the learning task, leading to computational bottlenecks. In addition, measured data is inherently noisy and this introduces uncertainty into the learning problem. Your research focus will be in tackling these issues through the development of robust tensor-based probabilistic machine learning methods for learning nonlinear dynamics from noisy data.
The DAI Lab DeTAIL is led by Kim Batselier and Borbála Hunyadi. You will work in the faculty of Mechanical, Maritime and Materials Engineering (3mE) at the Delft Center for Systems and Control (DCSC). The 3mE Faculty carries out pioneering research, leading to new fundamental insights and challenging applications in the field of mechanical engineering. From large-scale energy storage, medical instruments, control technology and robotics to smart materials, nanoscale structures and autonomous ships. The foundations and results of this research are reflected in outstanding, contemporary education, inspiring students and PhD candidates to become socially engaged and responsible engineers and scientists. The faculty of 3mE is a dynamic and innovative faculty with an international scope and high-tech lab facilities. Research and education focus on the design, manufacture, application and modification of products, materials, processes and mechanical devices, contributing to the development and growth of a sustainable society, as well as prosperity and welfare.
TU Delft offers DAI-Lab PhD-candidates a 5-year contract (as opposed to the normal 4-years), with an official go/no go progress assessment after one year. Approximately a fifth of your time will be allocated to developing ground breaking learning materials and educating students in these new subjects.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3217 in the fifth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.
To apply, please submit to application-3mE@tudelft.nl by 30 August 2020:
- 1-page Motivation letter,
- your CV;
- a (part of your) M.Sc. thesis or a paper that you have written, in which you demonstrate your writing skills.
Please highlight in your motivation letter and/or CV examples of projects and achievements that demonstrate your relevant competences.
All these items should be combined in one PDF document. When applying for these positions, please refer to vacancy number TUD00258.
A pre-employment screening can be part of the application procedure.
For information about these vacancies and the selection procedure, please contact Kim Batselier, Assistant Professor, email: email@example.com.
Web site for additional job details
- Completed a relevant MSc degree in an applied sciences field relevant to PhD research.
- Demonstrated competences in one or more of these categories: numerical linear algebra, statistics, machine learning, signal processing, control theory, or another relevant field.
- An affinity with teaching and guiding students.
- A proven record and interest in further developing your modelling, programming, analytical and scientific writing skills.
- An affinity with cities and transportation.
- Proficiency in expressing yourself verbally and in writing in English.
- The ability to work in a team, take initiative, are results oriented and systematic.
EURAXESS offer ID: 532018
Posting organisation offer ID: 292477
The responsibility for the jobs published on this website, including the job description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.
Please contact firstname.lastname@example.org if you wish to download all jobs in XML.