Postdoc position in Deep-Learning for Humanoid Robots - [ Postdoc ]

Workplace: Genova, IIT
Added on: 08/08/2019 - Expires on: 30/10/2019

The iCub Tech Facility at Istituto Italiano di Tecnologia (IIT) is seeking to appoint a postdoc in Deep-Learning for Humanoid Robots.

The selected candidate will join the interdisciplinary team of the iCub Tech team. She/he will contribute to the design and implementation of Deep-Learning based Applications for Humanoids.

Primary function of the position:

Contribute broadly to the development team, responsible for machine learning, and new technology development focused on Deep-Learning based Applications for Humanoids.

We are looking for a talented and enthusiastic postdoctoral researcher who will join our team to study algorithms for robotics with a focus on autonomous learning. The successful candidate must excel in a high-energy, focused, small-team environment, be able to initiate and drive new research and development directions.

As part of the development team, immediate responsibilities include:

  • Exploration and development of machine learning algorithms such as unsupervised learning, skill acquisition, active learning, object detection and segmentation, scene understanding, semantic segmentation and autonomous exploration.
  • Fully integrating machine learning into core robotic applications.

Additional responsibilities include:

  • Understand and modify in-house integrated machine learning algorithms.
  • Design and apply machine-learning algorithms to novel, robotic applications.

Required skills:

In order to adequately perform the responsibilities of this position the candidate must have:

  • PhD in Computer Science, Robotics, Computer Vision or related fields;
  • M. Sc. in Computer Science, Physics or related fields;
  • Ability to analyze, improve and propose new algorithms/solutions;
  • Solid understanding of statistics, machine learning, and Deep Learning algorithms
  • Good programming skills;
  • Experience with Python is required;
  • Hands-on experience with deep learning frameworks such as Tensorflow, Theano, Caffe, and/or Torch is required;
  • Good communication skills and ability to cooperate within a team;
  • Creative, proactive and collaborative attitude.

Desirable skills:

  • Experience with C/C++ is ideal
  • Familiarity with robotic middleware (e.g. YARP, ROS) and development tools (e.g. CMake and Git);
  • Hands-on experience with CNNs, RNNs, and LSTMs is ideal

The successful candidate will be offered a salary commensurate to experience and skills.

Please apply by October, 30 2019, by sending your application to quoting BC77385 - Post Doc position on Deep Learning for Humanoid Robots in the e-mail subject. Your application shall contain a detailed CV, university transcripts, a research statement and the contact information of two referees.

Fondazione Istituto Italiano di Tecnologia ( is a non-profit institution created with the objective of promoting technological development and higher education in science and technology. Research at IIT is carried out in highly innovative scientific fields with state-of-the-art technology.

Istituto Italiano di Tecnologia is an equal opportunity employer that actively seeks diversity in the workforce.

Please note that the data that you provide will be used exclusively for the purpose of  professional profiles’ evaluation and selection, and in order to meet the requirements of Istituto Italiano di Tecnologia.

Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security.

Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 - email:  dpo[at]



IIT's website uses the following types of cookies: browsing/session, analytics, functional and third party cookies. Users can choose whether or not to accept the use of cookies and access the website. By clicking on "Further Information", the full information notice on the types of cookies will be displayed and you will be able to choose whether or not to accept them whilst browsing on the website
Further Information
Accept and close