Doctoral Student Position within Probabilistic Signal Processing and Machine Learning
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Are you an enthusiastic student with intrests in Kalman filters, Bayesian statistics, Monte Carlo methods, or Gaussian processes? Are you looking for an exciting doctoral student position as part of a vibrant world-class researcher team? Look no further – our research group conducts cutting-edge research for the benefit of both humanity and industry.
The Sensor Informatics and Medical Technology (Sensori-informatiikka ja lääketieteellinen tekniikka) research group focuses on the development of probabilistic (i.e. Bayesian) signal processing and machine learning methods especially for health and medical applications. Other applications include positioning and tracking systems as well as industrial measurement and control systems. Although the research is motivated by applications, group’s research also spans development of general statistical methodology as well as theoretical analysis of the methods.
The position is a fully funded PhD student position and the selected person will be appointed for a fixed term appointment starting in late 2019 or early 2020 (negotiable). The work will be done under supervision of Professor Simo Särkkä.
The position is available in the growing Sensor Informatics and Medical Technology research group. We aim to carry out original high-quality research and continuously publish in top journals and conferences of the field. We have an extensive international collaboration network, which will facilitate the mobility of our researchers to leading research groups abroad, and vice versa. Our group is located at the Department of Electrical Engineering and Automation at Aalto University in Helsinki capital region at it is also affiliated with the Finnish Center for Artificial Intelligence (FCAI).
Possible research topics include, but are not limited to:
- Bayesian filtering/smoothing and machine learning methods for biomedical signal processing and medical imaging applications. Promising methods have been, for example, Kalman filters and Gaussian process regressors/classifiers. Deep networks and GPs have also been successfully used.
- Sensor fusion methods for motion tracking and positioning. The used sensors include, for example, inertial and magnetic sensors, and the methodology typically includes non-linear Kalman filters/smoothers and particle filters/smoothers along with methods like MCMC.
- New computational methods and models for highly non-linear and non-Gaussian large-scale spatio-temporal stochastic systems. This kind of methods can be based on, for example, GPU-accelerated parallelization methods, new nonlinear Kalman-type of methods, expectation-propagation, posterior-linearization, sigma-point methods, or sequential Monte Carlo.
- New computational methods and models for machine learning for signal processing. Examples of such methods and models are state-space GP methods, SPDE methods for GPs as well as hierarchical / deep models, probabilistic programming languages, graphical methods, etc.
In addition to research work, persons hired are expected to participate in the supervision of students and teaching following the standard practices at the department.
What we are looking for
- M.Sc. or equivalent in a related field.
- Experience or interest in Bayesian filtering, probabilistic machine learning, or the application fields.
- Strong programming skills in languages such as Matlab, Python, or C/C++ are required.
- Knowledge of machine learning related packages would be beneficial: Tensorflow/Pytorch, Numpy, etc.
- Proficiency in English (oral and written) required
What you get
The starting salary for a doctoral student position is 2518 €. In addition to the salary, the contract includes occupational health care benefits, and Finland has a comprehensive social security system. The annual total workload of teaching staff at Aalto University is 1 624 hours. The position is located at the Aalto University Otaniemi campus which can be easily reached via the Metro-train.
Application material and procedure
Please apply through the electronic recruitment system link Apply now!, no later than October 31, 2019, Finnish time. Early submission is strongly encouraged, as applications will be processed and evaluated upon arrival. Include your CV with names and contact information of two senior academics willing to give more information and list of publications.
Short-listed candidates may be invited for an interview on the Otaniemi campus of Aalto University in Espoo or for an interview conducted via Skype. Should there be a lack of eligible outstanding applicants, Aalto University reserves the right to leave the position open, to extend the application period and to consider candidates who have not submitted applications during the application period
Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with nearly 11 000 students and a staff of more than 4000, of which 400 are professors. Our campuses are located in Espoo and Helsinki, Finland.
The greater Helsinki region is a world-class information technology complex, attracting leading scientists and researchers in various fields of computer science. Helsinki is regularly highly graded in world city rankings, such as global livability ranking by The Economist (Ranked eighth in 2014). As a doctoral student, you will enjoy sophisticated, high-quality and vibrant life of Nordic charm.