Opendata, web and dolomites

EnergySequence SIGNED

Building data scientist to help us dive deep into the very large amount structured time series data pertaining to building energy use

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 EnergySequence project word cloud

Explore the words cloud of the EnergySequence project. It provides you a very rough idea of what is the project "EnergySequence" about.

12    innovative    assist    statistical    rapid    ing    cutting    scientis    demand    ai    conservation    first    juggle    sophisticated    remotely    responsibilities    assure    schedules    software    closely    virtual    scientist    series    gleaned    sequencing    verification    searches    pertaining    structured    grant    cooling    startup    integration    career    analys    scalable    data    devised    shifting    contexts    recruitment    developers    establishing    recommendations    energy    switch    input    ratios    disaggregation    skills    abnormal    ideal    recommendation    multiple    algorithms    edge    assessing    intelligence    insights    heating    platform    deployment    deep    building    limited    load    candidate    time    site    team    consumption    optimal    prototyping    innovation    literature    models    base    forecast    stop    assisting    amount    audit    fraction    start    concerned    code    rule    machine    model    engineers    automate    responsible    comfortable    perform    baseline    learning    saving    efficiency    algorithmic    dive    asessment   

Project "EnergySequence" data sheet

The following table provides information about the project.

Coordinator
VATIA ENERGIA SL 

Organization address
address: CALLE MARIA CURIE 8 EDIF. B PARQUE TECNOLOGICO DE ANDALUCIA
city: MALAGA
postcode: 29590
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website https://www.bettergy.es/en/
 Total cost 68˙000 €
 EC max contribution 68˙000 € (100%)
 Programme 1. H2020-EU.2.3.2.2. (Enhancing the innovation capacity of SMEs)
 Code Call H2020-INNOSUP-02-2016
 Funding Scheme CSA
 Starting year 2017
 Duration (year-month-day) from 2017-09-01   to  2018-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    VATIA ENERGIA SL ES (MALAGA) coordinator 68˙000.00

Map

 Project objective

We are looking for a Building data scientis to help us dive deep into the very large amount of structured time series data pertaining to building energy use and help automate insights gleaned from sophisticated model based energy analys into scalable rule based recommendation system

The Building Data Scientist will be responsible for modelling, but will work closely with Energy Efficiency Engineers and the Software Developers, also assist on new R&D initiatives as needed.

As a member of an innovative startup on a rapid growth path, the ideal candidate must be able to juggle multiple responsibilities, be comfortable in developing cutting-edge statistical and machine learning algorithms as well as have the ability to switch contexts rapidly between research literature searches, rapid algorithmic prototyping, as well as assisting in code testing and deployment.

We have devised a career path for the 12 month grant to assure the best integration in the team, skills development and innovation results for the project.

We expect an important impact resulting from the recruitment as far as the intelligence analysis features of the software platform is concerned. Innovation resulting from the ability to assess energy efficiency remotely without going on site, therefore at a fraction of the time and cost. This innovation will be supported by the development of AI algorithms and building energy models using limited input information.

AI algorithms will enable us to perform a virtual energy audit, assessing energy end-use disaggregation (heating and cooling), time schedules, etc then establishing first energy saving recommendations measures: load shifting, abnormal consumption, energy equipment start and stop optimal sequencing, etc

Building energy modelling determining the building energy demand and consumption forecast, identify the building energy baseline for energy conservation measures asessment and verification, and the energy base load, establishing energy ratios

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "ENERGYSEQUENCE" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "ENERGYSEQUENCE" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.2.3.2.2.)

EEN OUEST H2020 (2020)

Entreprise Europe Ouest H2020

Read More  

INNOSUPPORT (2020)

Innovation Management Support for SMEs

Read More  

SIM Crowd (2019)

Social Innovation Matched Crowdfunding (SIM Crowd)

Read More