ENTRY LEVEL/JUNIOR DATA ENGINEER

Innaxis is currently seeking for a Data Engineer (Entry Level/Junior ) to join its deployment team, Tadorea. We are based in Madrid, Spain. We look for talented and highly motivated data engineers who want to pursue and lead a career outside of the more mainstream, conventional alternatives. Individuals with a great dose of imagination, problem solving skills, flexibility and passion are encouraged to apply.

As a Data Engineer, you will help the team to design and integrate complete solutions for Big Data architectures; from data extract, load and transform processes until data storage, life cycle, management and delivery for analysis. Always making use of the latest technologies and solutions for the ultimate performance.

Skills wanted
Data Engineers at the Innaxis spin off, work very closely with the rest of the Data Science team, so a broader knowledge and a varied skillset will be very much appreciated.Candidates would be evaluated according to the following items (fulfilling the complete list is not a mandatory requirement)

  • University degree on Computer Science
  • MSc or PhD not required but positively evaluated
  • Professional experience is not a must, although it might be positively evaluated.
  • Proficient in a variety of programming languages, for instance: Python, Scala, Java, R or C++ and up to date on the newest software libraries and APIs, e.g. Tensorflow, Theano.
  • Experience with acquisition, preparation, storage and delivery of data, including concepts ranging from ETL to Data Lakes.
  • Knowledge of the most commonly used software stacks such as LAMP, LAPP, LEAP, OpenStack, SMACK and similar.
  • Familiar with some of the IaaS, PaaS and SaaS platforms currently available such as Amazon Web Services, Microsoft Azure, Google Cloud and similar.
  • Understanding of the most popular knowledge discovery and data mining problems and algorithms; predictive analytics, classification, map reduce, deep learning, random forest, support vector machines and such.
  • Continuous interest for the latest technologies and developments, e.g. blockchain, Terraform.
  • Excellent English communication skills (written and oral). It is the working language at Innaxis.
  • And of course, great doses of imagination, problem solving skills, flexibility and passion.
Benefits
The successful candidate will be offered a position as a Data Engineer, including a unique set of benefits:

  • Being part of a young, dynamic, highly qualified, collaborative and heterogeneous international team.
  • Flexible working environment, schedule and location.
  • A horizontal hierarchy, all researchers’ opinions matter.
  • Long term and stable position. Innaxis is steadily growing since its foundation ten years ago.
  • Salary adjusted to skills, experience and education.
  • The possibility to develop a unique career outside of mainstream: academics, private companies and consulting.
  • No outsourcing whatsoever, all tasks will be performed at Innaxis offices.
  • An agile working methodology; Innaxis recently implemented JIRA/Scrum and all the research is done on a collaborative wiki/Confluence.
Applying
IMPORTANT: Interested candidates should send their CV, together with a interest letter (around 400 words) and any other relevant information supporting their application to recruitment@innaxis.org .You will be contacted further and a personal selection process will start. We deal personally with all candidates.

EU Door-to-Door Mobility Workshop – Abstracts

  • Session 1. Challenges of a data-driven model

The current state of mobility in Europe – University of Westminster
The foundations of the DATASET2050 model are described in this presentation, along with some of the corresponding data sources used in its construction. Using mobility, we show roughly how far from the target we are currently in Europe, with optimistic and less optimistic scenarios. We present the order of magnitude of the trip segments and introduce the main problematic. Finally, we have a brief look at how uncertainty is playing a key role right now in transportation with the creation of buffers – pure interplay between supply and demand.

Meeting the passenger’s demand: current and future – Bauhaus Luftfahrt
This presentation illustrates the passenger-centric approach taken within the DATASET2050 project by developing current demand profiles. It elaborates different aspects influencing passenger demand such as age, income, household structure, or technological affinity. Based on the analysis of European data, a range of passenger profiles and respective characteristics are derived. These determine the requirements passengers have during their journey and hence the time spent in different processes. Furthermore, data on European mobility behaviour yields different archetype journeys for these passengers.

Developing a new model for European mobility – Innaxis
The DATASET2050 mobility model is a mathematical framework aiming to represent the European door-to-door transportation network. The model has a stochastic approach inherited from complex networks theory, but is ultimately implemented using data science tools. This presentation will address how journey lengths are estimated as an aggregation of multiple random sub-processes and how decision networks are driven by stochastic supply and demand profiles. Several candidate mobility metrics will also be discussed and how the model can be used, to some extent, to analyse future scenarios.

  • Session 2. Further exploring the journey process phase by phase – where are the efficiency gains?

Door-to-kerb – Prof. Dr. Kai Nagel, Technical University of Berlin
The MATSim (Multi Agent Transport Simulation) project is involved with the microscopic simulation of individual travellers at the regional or even national scale. The approach starts from a synthetic population where real humans are replaced by statistical equivalents, builds full daily schedules for them, and follows them through their day with a special focus on the transport system. The system also allows us to run detailed analysis tasks; for example, investigating the accessibility of households to all kinds of services by all means of transport. Clearly, it would also be possible to follow synthetic persons from home or workplace to an airport, or from airport to workplace or home. This presentation will demonstrate current capabilities and discuss possible extensions to MATSim.

Kerb-to-gate – Dr. Genovefa Kefalidou, Horizon 2020 PASSME project
Understanding passenger, airports and airlines’ needs promptly, transforming them into intelligence and adjusting services based on this intelligence is now even more demanding. PASSME is an EU-Horizon 2020-funded project in which we aim to provide innovations to modern journey challenges while at airports. We work on innovations to enhance passengers’ experiences (including reducing stress), providing real-time personalised information, improving interiors and luggage flow and forecasting passenger flow. We identify that passenger needs intertwine strongly with airport and airline needs, manifesting opportunities to build a relationshipamongst all these stakeholders through the use of mobile, back-end and situated innovations. This relationship demands to be maintained throughout the different airport touch points (e.g. kerb-to-gate) to facilitate and optimise the journey process as knock-on effects are transferred between phases, often causing further delays and dissatisfaction.

Gate-to-gate – Steve Williams, NATS
This presentation considers a selection of SESAR concepts, considering changes from flight plans to business trajectories and from distance-based to time-based spacing, also including extended arrival management horizons and system-wide information management (SWIM). It considers the relevance of SESAR to future transport goals: what could SESAR provide to other transport modes, what are the limitations, and why are the limitations unlikely to change? The importance of air traffic management data accuracy is also discussed, and why data are much more precise once an aircraft has left the ground.

  • Session 3. Looking ahead to 2035 and 2050

Futures near and far – Christoph Schneider, Munich Airport
There are many potentially disrupting developments that add a lot of uncertainty when it comes to predicting mobility in 2035. The ACARE mobility vision does not contradict any of these trends. The European aviation market may appear to mature wrt growth rates, but absolute growth will most likely still be huge. Airport capacity is set to be the limiting factor with little hope of being coped with. Munich Airport is very actively engaged in activities to increase capacity, improve intermodality and enhance passenger experience by innovative digital products – these areas are common denominators for mobility in 2035.

“State-of-art in ATM Resilience” workshop prior to SIDs | 24th Nov, Madrid

Before the 2014 SESAR innovation days SIDs officially kicks off in Madrid, there will be a workshop which will open the debate around the state-of-art in the context of resilience in the Air Transport System and its operations.

At the workshop we’ll discuss the recent discoveries made in the field by the FP7 project consortium “Resilience2050,” along with inputs from other teams conducting research in the area. To enhance the workshop and collaboration, there will also be a social and networking event to discover historical Madrid city-centre, and its “resilience” to time, wars and other disturbances. The networking session will provide a great opportunity to get to know colleagues in the field of ATM and especially Resilience prior to the SIDs forum.

Date: 24th November from 14:00 to 18:00, social event between 19:00 and 20:30

Location: Madrid, UPM university- ETSIA building (google maps), social event finishing around here.

Registration to worlshop+social event is free and still open but with very limited number of places: hurry up! register by clicking here!

 

Visualisation Technologist Internship

Innaxis is seeking a Visualisation Technologist to join the research and development team for aviation projects. As a member of the team, you join a very interdisciplinary group of researchers, scientists, mathematicians and engineers who work for private companies and public institutions to solve the most challenging problems using the most of their data.

A mixture of creativity and technical skills are required to complement the skill set of a team that has worked in the last 5 years establishing landmarks in terms of network performance analyses across different areas within the aviation sector.

We are looking for a talented individual to complement the existing research threads on visualising large data sets in an innovative way to provide new insights on the performance of complex systems, including the development of interactive dashboards to enable the real time analysis of complex phenomena. Being part of a team entails working with other skilled researchers who are currently focused on knowledge discovery, data mining and big data infrastructures.

Requirements are as follows:
  • Degree in Computer Science or similar (mathematics, physics) with outstanding background and experience in programming.
  • Solid design and conceptual representation skills.
  • Tasteful and artful conception of data visualisation and infographics.
  • An existing portfolio would be very appreciated and very positively evaluated
  • Passion for data visualisation on top of current thinking and trends
  • Location: Either Madrid (Spain) or Linz (Austria)

Technical skills which may be relevant in the evaluation:

  • Web technologies: HTML, CSS3, JavaScript, …
  • Basic knowledge of database technologies and use: MySQL, MongoDB, JQuery
  • Proficiency in Java
  • Experience in any of the following libraries: d3.js, dc.js, Raphaël, …
  • Other visualisation technologies experience is appreciated
  • Any other programming language is a plus: Python, Perl, C, R, Matlab …

Innaxis offers:

  • Internship 6 months, with an opportunity to become a part of the team after internship conclusion
  • Immediate start within a highly qualified and collaborative international team with innovative thinking and working methodology focused on the development of large scale research and innovation projects.
  • Interesting salary as a function of skills, experience and education.
  • Flexibility and good working conditions

Interested candidates should send their detailed CV and relevant information to innovation@innaxis.org.

Roadmap for data-driven applications, from a concept to a fully integrated system

Doubtless Data Science and Big Data applications have been growing fast in the last years, the blooming of new data sources and the emergence of accessible and affordable cloud infrastructures have contributed widely to this movement. However only a few applications reach the necessary level of maturity to become fully functional systems. Most of data driven applications reach its maximum level of maturity as a “proof of concept,” and one of the main reasons being it does not have a solid integration program with current systems or a successful validation plan.

The path from raw data to wisdom is long and complex. Moving from data to information requires comprehension on data relations and the overall context. Then, knowledge is reached only after fully understanding the patterns within information. Finally, it is required to get deep into the details (the underlying principles), to gain insight and be able to move from knowledge to real and “applicable” wisdom.

There are three pillars in any Data-Driven application, namely: Data Acquisition (DA), Information Processing (IP) and Knowledge Discovery (KD). The Data Acquisition should cover not only the technical aspects of consuming services or data sources with different formats, coverage or scope but also tackle the sociological, legal and limiting aspects of every data source (e.g. data provenance). The Information Processing should be built over a solid mathematical framework, from Data Mining algorithms to Simulation Tools. Information Processing should also provide answers in terms of performance and precision to support the application concept. Lastly, Knowledge Discovery should serve as a interface from processed data to human perception, from metrics to representation of those (e.g. dashboards). In some cases integration of those into the current system may be critical.

The application must be developed at the three fronts simultaneously, starting with a concept, a purely speculative idea, to a proof of concept, a prototype application tested only over a simplified set of data. Then the proof of concept should be further tested in a laboratory environment, in which data samples are produced artificially to feed the application and carry on performance and reliability tests and then leveraged into a relevant environment. In a relevant environment the application should be capable of working with real-time data feeds although not yet at an operational level, and robustness and stability should be assessed at this stage. Finally, applications should be moved for a relevant environment to the actual operations.

Presenters needed for Agent-Based Modelling Webinar

The ¨Using Qualitative Data to Develop Rules for Agent-Based Modelling¨ webinar is to be hosted in early June. The webinar coordinators, Rachel Aldred from the University of Westminster and Melania Borit from the University of Tromsø Norway, are seeking presenters and participants.

The webinar will focus on work in progress that is using qualitative data to develop rules for ABM. The format is likely to involve short (10-20 minute) presentations as well as time for discussion, comments, and reflection.

If you are interested in offering a short presentation or joining in the discussions following the presentations, please email Rachel at r.aldred@westminster.ac.uk and Melania at melania.borit@uit.no. Please include the reasons for your interest and if you will be offering a presentation. Also please note that you will need reliable internet connection, a headset, and an updated Java program enabled on your computer to participate.

POEM Project awarded by SESAR JU

The Passenger-Oriented Enhanced Metrics (POEM) project, led by the University of Westminster in partnership with Innaxis establishes a new passenger-centred performance framework and simulation model for air transport. The model allowed the exploration of novel flight and passenger prioritisation scenarios whilst the performance framework allowed the analysis of different trade-offs between the flight-centric and passenger-centric metrics. Furthermore, using novel techniques of data science analysis, the project shed light on delay propagation through the network and made clear the very different roles that some elements of the air transportation system play from the passenger perspective, as compared with the more usual flight performance perspective.

This performance framework is especially relevant in the context of the 4 hours door-to-door performance goals envisioned by FlightPath2050 and core to the technological developments in air transport for the next decade.

POEM received one of only two “Oustanding Project” awards from SESAR, judged by a jury composed of SESAR JU members, including industry and ANSP representatives. The prize was presented during the 2014 SESAR Awards Ceremony, which took place alongside the 2014 World ATM Congress in Madrid, 3-6 March. This prize recognised the excellence of the project and its novel contributions to SESAR, as highlighted by Mr Claude Chêne, Executive Director of the SESAR Joint Undertaking, who presented the prize to Andrew Cook, coordinator of the POEM consortium.

Innaxis is very proud of POEM for its significant contribution to passenger-centricity and complexity science, a completely novel approach in air transport research.

Marketing and Communications Lead

[Filled! Check back here for other future opportunities.]  Innaxis, an innovative scientific research foundation and institute, invites highly qualified candidates in the field of communication and advertising with skills in technical communication to apply for the role of Marketing and Communications Lead of the organisation. Innaxis focuses on research programmes in aviation and other highly technical activities, working for different stakeholders in these highly specialised fields. Cutting edge/new applications and exploration of delay propagation, capacity analysis, fuel and emission modelling, information encryption and data science in aviation are areas of research in which the organization is currently engaged.

 

Functions

The Marketing and Communication Lead (MCL) will be responsible for ensuring the quality of all Innaxis documentation and communication. While the content of scientific documentation is provided by other colleagues, the MCL will review, edit, and modify these documents for greater readability, as well as format the document according to external and internal guidelines. These documents include technical deliverables and, while background and experience in technical fields is certainly needed and expected, no deep technical understanding of the content is required.

The MCL will also be responsible for the online communication strategy including the maintenance of blogs, LinkedIn pages and groups, including tracking of the number of visits and general progression of the visibility of Innaxis communications. The MCL will also be responsible for providing guidelines to the team in terms of communication.

 

Skills

  • Excellent written communication skills in technical domains
  • Fluent user of the main online marketing tools, including social media
  • Innovative ‘out-of-the-box’ thinker that creates customized solutions
  • Fluent in use of the main MS Office tools
  • Self motivated team worker that is driven to achieve success
  • Affinity and motivation for technical domains, ideally for the aviation field
  • Native English speaker. Spanish language skills are a plus.
  • WordPress blog and wiki management experience as well as online technical skills and understanding of SEO and SEM very appreciated

 

We offer

  • An immediate start within a highly qualified and collaborative international team that incorporates innovative thinking and a working methodology focused on the development of large scale research and innovation projects
  • Attractive salary. Part-time position. Flexibility and good working conditions.

 

Interested candidates should send their detailed CV and relevant information to:

innovation@innaxis.org

Madrid, January 2014

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Alberto´s view on Agent-based modeling

Editor´s Note: At Innaxis we are starting a new series that involves contributions from individuals that work at Innaxis. Below is our first contribution from Alberto.

It’s nice to learn new things every once in a while. I’m not a mathematician but I am definitely intrigued by the way some things work and how they can be studied. Recently I have been investigating lately about agent-based modeling.

Agent-based modeling is a relatively new science that is being used to analyse systems that are composed of many elements. In the Cassiopeia project, these elements are the airplanes, airlines, airports, air navigation service providers, and the passengers.

The nice thing about the agent-based models (ABMs) is that we can assign some decision making attributes to each element and see what happens when we run the program. Another important aspect of ABMs is that we can design the strategy of some elements, since sometimes what’s best for a single element is not the best for the team.

To put this in context, we can look at Russell Crowe’s character ¨John Nash¨ in the movie “A Beautiful Mind.¨ In one scene, his character explains that a group strategy does not necessarily require each member to achieve best possible outcome individually (which was in their case, for no one to approach the blonde woman). Often times when studying aircraft, we need to approach problems in a similar way- figuring out the group strategy that suits everyone in a collective sense. An example of this would be the distribution of delay amongst all the aircraft rather than having a few aircraft support the entire delay. This becomes a bit challenging as it would be much more easier and convenient to have solutions be based on key individual factors (one man approaches the woman; few aircraft bear the burden of delay), however we learn and demonstrate in the Casseiopeia project that agent-based modeling is actually the best way to resolve situations. In the end more is benefited from a involving multiple elements rather than just a few.

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