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Positions in Gaussian Processes for Big Data at IDSIA, Lugano, Switzerland

The Dalle Molle Institute for Artificial Intelligence (IDSIA) opens one PhD and one PostDoc position for the project State space Gaussian processes for big data analytics (GAP), supported by Swiss National Science Foundation NFP75 “Big Data” grant. The deadline for this post is 20th, December, 2016, however we encourage applications before this date.

Description

Gaussian processes (GPs) are part of non-linear Bayesian non-parametrics. Its being non-linear means that it can capture very general trends in multi-dimensional data; non-parametric means that it makes very weak assumptions, so it leads to more reliable models; and being Bayesian means that there is solid theory behind it on which we can do maths to derive algorithms and prove their properties. GPs are an emerging tool in machine learning, and yet large data problems are mostly uncharted territory for them: in fact, they can only be applied to at most a few thousand training points n, due to their O(n^3) time and O(n^2) space required for learning. The main goal of this project is to fill the gap by deriving a principled, accurate, approximation of GPs that can exploit all the available data while sharply decreasing space and time complexity, so as to allow us to apply GPs to big data. More generally speaking, the project will be a mix of deep theoretical work and smart implementation, as well as application to two complex and important domains.

Duties

The successful applicants will work on the theoretical development of the algorithms as well as their implementation within a skilled and motivated team of scientists dedicated to the project.

PostDoc Requirements

  • This position is for a young researcher.
  • Master and PhD with top grades/honors in control engineering, mathematics, machine learning, statistics, or other quantitative fields.
  • Strong mathematical background: knowledge and experience in topics such as Gaussian processes, Bayesian statistics, (partial) differential equations, estimation for dynamical systems, Kalman filtering/smoothing and optimization.
  • Good record track of high quality publications in well-recognised international journals or conferences (eg., IEEE/ACM ones) on the mentioned topics.
  • Strong programming skills and knowledge of specialised mathematical/statistical environments, such as MATLAB and R. Strong analytical skills, such as problem solving and logical thinking.
  • Very good written and oral communication skills in English.
  • Ability to work in a team and in a collaborative environment. Autonomy.

PostDoc Offer

  • Fixed-term position for 2 years, with possibility of prolongation.
  • Attractive salary, in line with Swiss standards.
  • International working environment. Travel support to participate in high quality conferences, workshops and schools.

PhD Requirements

  • Master with top grades/honors in control engineering, mathematics, machine learning, statistics, or other quantitative fields.
  • Strong mathematical background: knowledge and experience in topics such as Bayesian statistics, (partial) differential equations,
  • estimation for dynamical systems, Kalman filtering and optimization.
  • Excellent grades, strong programming skills and knowledge of specialised mathematical/statistical environments, such as MATLAB and R.
  • Strong analytical skills, such as problem solving and logical thinking.
  • Very good written and oral communication skills in English and good academic writing.
  • Ability to work in a team and in a collaborative environment.
  • Autonomy.

PhD Offer

  • Fixed-term position for 4 years.
  • Salary as from the Swiss NSF regulations.
  • International working environment.
  • Travel support to participate in high quality conferences, workshops and schools.

The requirements for these functions are published within the "Direttive interne SUPSI" (direttiva 7A, Art. 2) as well as in the "Regolamento del personale SUPSI" on the website www.supsi.ch (follow SUPSI, Documenti ufficiali).

For further information and application, please contact:

Alessio Benavoli, senior researcher
This email address is being protected from spambots. You need JavaScript enabled to view it.

Applicants should submit the following documents: curriculum vitae (for PostDoc with list of publications), list of exams with grades obtained during the Bachelor and the Master of Science, letter of motivation, three references (e-mail addresses).