To develop an automatic model updating technique that registers the real-world data (point clouds and images) on the existing BIM model (i.e. a design model or a previous as-is model), matches real with virtual elements, detects missing or additional objects and relationships, and updates existing model geometrical properties and relationships to match those derived from the real-world data. The ESR must: (1) define the properties and relationships to be updated; (2) devise the technique; (3) implement and test a prototype; (4) drive the technology transfer process through development and IP exploitation with partner LocLab Consulting.
The ESR will develop a prototype implementation of the model updating technique capable of automatically updating the number, type, location, dimensions, relationships and textures of model objects. It will also borrow learning strategies explored by ESR 1 to insert additional real objects that are not present in the virtual model. To do so, the fellow will require extensive training on computer vision, machine learning and computational geometry (at STFD), modelling standards and geometry enrichment (Technion – Israel Institute of Technology). A secondment to LocLab Consulting is planned where the ESR will develop the potential for application of this technique to a real application scenario.
This ESR position is part of the CBIM network, a consortium of European partners with complementary world-leading expertise from academia and industry, is offering 14 fully funded PhD and one Post Doc position for highly talented people who are eligible for study at any one of its partner universities. Each ESR will be employed full time at one of the CBIM partner universities or at one of the three CBIM beneficiary companies. Those employed directly by the universities will enrol for PhD study at the same university; those employed by partner companies will enrol at one of the five universities for external PhD studies. CBIM is funded by the EU Horizon 2020 program under the Marie Skłodowska-Curie Innovative Training Network call under grant no. 860555. Please see https://cbim2020.net.technion.ac.il/
Recruitment, Eligibility and Mobility
Successful candidates will be employed for a maximum period of three years full-time equivalent and receive a generous financial package plus an additional mobility and family allowance according to the rules for Early Stage Researchers (ESRs) in an EU Marie Sklodowska-Curie Actions Innovative Training Networks (ITN). A career development plan will be prepared in accordance with his/her supervisor and will include training, planned secondments and outreach activities in partner institutions of the network. The ESR fellows are supposed to complete their PhD thesis by the end of the 3rd year of their employment.
All researchers recruited in a Marie Sklodowska-Curie ITN must be Early-Stage Researchers (ESRs). An ESR shall, at the time of recruitment by the host organisation, be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree.
Researchers are required to undertake transnational mobility (i.e. move from one country to another) when taking up their appointment. One general rule applies to the appointment of researchers: on the date of recruitment by the host beneficiary, researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of their host beneficiary for more than 12 months in the 3 years immediately prior to the reference date. Note that the mobility rule applies to the beneficiary where the researcher is recruited, and not to beneficiaries to which the researcher is sent or seconded. Date of Recruitment normally means the first day of the employment of the fellow for the purposes of the project (i.e. the starting date indicated in the employment contract or equivalent direct contract).
Researchers can be of any nationality.
There is no age limit.
Applicants must hold a research (thesis) Master’s degree in engineering, architecture or computer science.