This is Airbus Internships

We offer internships in a variety of career fields, with a large offering of Engineering (Mechanical and Industrial) as well as Business Operations (Accounting/Finance, Marketing, etc.

Make Your LinkedIn Soar Courtesy of AIRBUS

Take the time to make it spectacular; invest in yourself. Fill out every single section. LinkedIn will actually measure the “completeness” of your profile and provide suggestions of how you can make it even better. Avoid buzzwords! i.e. (creative, strategic, analytical, etc.) Be unique and find words that aren’t overused. Instead, look at job descriptions that you are interested in to see what words they use – those are the words you should be using on your profile. Use a custom URL for your profile – it’s much easier to market your profile with a custom URL (i.e. linkedin.com/yourname) How to make one? Edit profile \u3e edit public profile & URL \u3e personalize URL for profile Show some personality – make it unique, make it yours

Vertical sub-contracting relationships strategy, the Airbus First-tier suppliers\' coordination

This paper analyzes the transformations of industrial vertical relationships, and more particularly the duality of the coordination modes within new industrial architectures. The paper aims to characterize relationship between the architect and the first-tier suppliers according to the strategic degree of their competence. Two models of coordination arm\'s length and systems integration coexist within the same industrial architecture. The recourse to one or the other varies according to the policy of purchase and the strategic degree of the sub-contracted subsystems. Thus we will analyze the system of subcontracting of Airbus by focusing to the importance of the purchasing policy. The argumentation articulates in two parts. The first one considers the vertical subcontracting relationships in the framework of complex productions, by insisting on organizational aspects. The second one analyses the transformation of the \"Airbus\" productive system by focusing on purchasing process and the emergence of new First-tier supplier’s coordination modes.NAModularity – Systems Integration – Strategic competences – Purchasing Strategy – First Tier Suppliers – Airbus

Framework for Multi-Asset Comparison and Rapid Down-selection for Earth Observation Missions

Copyright © 2019 by Jerome Gilleron and Marc Muehlberg. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.Observing the Earth, whether it be from space or from the air, has become easier in recent years with the advent of new space-borne and airborne technologies. First, satellites constantly provide data about almost any point on the globe with varying resolutions and in various spectral bands. Second,Unmanned Aerial Vehicles (UAV) are becoming more readily accessible to the public and may be rapidly deployed to take high resolution images of ground features or areas of interest. Third, manned aircraft may be used to image large areas of land at a higher resolution than satellites and have been used regularly in disaster monitoring and surveillance missions. However, when multiple heterogeneous assets compete to perform a given aerial imaging mission, deciding which asset is better suited and/or less costly to operate in a timely manner is challenging. Every acquisition mode is different, resolution values are computed differently and there currently does not exist a common framework to compare UAV, manned aircraft and satellites. To address this challenge, this paper describes a methodology to rapidly compare various types of aerial assets (such as UAVs and manned aircraft) and space assets (such as satellites) to decide which one would be better able to perform an Earth observation mission depending on a set of requirements. To demonstrate the proposed methodology, this paper executes numerical simulations with three different representative scenarii in California

Malware classification using self organising feature maps and machine activity data

In this article we use machine activity metrics to automatically distinguish between malicious and trusted portable executable software samples. The motivation stems from the growth of cyber attacks using techniques that have been employed to surreptitiously deploy Advanced Persistent Threats (APTs). APTs are becoming more sophisticated and able to obfuscate much of their identifiable features through encryption, custom code bases and in-memory execution. Our hypothesis is that we can produce a high degree of accuracy in distinguishing malicious from trusted samples using Machine Learning with features derived from the inescapable footprint left behind on a computer system during execution. This includes CPU, RAM, Swap use and network traffic at a count level of bytes and packets. These features are continuous and allow us to be more flexible with the classification of samples than discrete features such as API calls (which can also be obfuscated) that form the main feature of the extant literature. We use these continuous data and develop a novel classification method using Self Organizing Feature Maps to reduce over fitting during training through the ability to create unsupervised clusters of similar ‘behaviour’ that are subsequently used as features for classification, rather than using the raw data. We compare our method to a set of machine classification methods that have been applied in previous research and demonstrate an increase of between 7.24% and 25.68% in classification accuracy using our method and an unseen dataset over the range of other machine classification methods that have been applied in previous research

Corporate responsibility & sustainability report

Descripció feta a partir de: 2014, el 3 setembre 2015

Calculating and communicating ensemble-based volcanic ash dosage and concentration risk for aviation

During volcanic eruptions, aviation stakeholders require an assessment of the volcanic ash hazard. Operators and regulators are required to make fast decisions based on deterministic forecasts, which are subject to various sources of uncertainty. For a robust decision to be made, a measure of the uncertainty of the hazard should be considered but this can lead to added complexity preventing fast decision making. Here a proof-of-concept risk matrix approach is presented that combines uncertainty estimation and volcanic ash hazard forecasting into a simple warning system for aviation. To demonstrate the methodology, an ensemble of 600 dispersion model simulations is used to characterise uncertainty (due to eruption source parameters, meteorology and internal model parameters) in ash dosages and concentrations for a hypothetical Icelandic eruption. To simulate aircraft encounters with volcanic ash, trans-Atlantic air routes between New York (JFK) and London (LHR) are generated using time-optimal routing software. This approach has been developed in collaboration with operators, regulators and engine manufacturers; it demonstrates how an assessment of ash dosage and concentration risk can be used to make fast and robust flight-planning decisions even 23 when the model uncertainty spans several orders of magnitude. The results highlight the benefit of using an ensemble over a deterministic forecast and a new method for visualising dosage risk along flight paths. The risk matrix approach is applicable to other aviation hazards such as SO2 dosages, desert dust, aircraft icing and clear-air turbulence and is expected to aid flight-planning decisions by improving the communication of ensemble-based forecasts to aviation

Real-time malware process detection and automated process killing

Perimeter-based detection is no longer sufficient for mitigating the threat posed by malicious software. This is evident as antivirus (AV) products are replaced by endpoint detection and response (EDR) products, the latter allowing visibility into live machine activity rather than relying on the AV to filter out malicious artefacts. This paper argues that detecting malware in real-time on an endpoint necessitates an automated response due to the rapid and destructive nature of some malware. The proposed model uses statistical filtering on top of a machine learning dynamic behavioural malware detection model in order to detect individual malicious processes on the fly and kill those which are deemed malicious. In an experiment to measure the tangible impact of this system, we find that fast-acting ransomware is prevented from corrupting 92% of files with a false positive rate of 14%. Whilst the false-positive rate currently remains too high to adopt this approach as-is, these initial results demonstrate the need for a detection model that is able to act within seconds of the malware execution beginning; a timescale that has not been addressed by previous work

Controllability and Design of Unmanned Multirotor Aircraft Robust to Rotor Failure

A new design method for multi-rotor aircraft with distributed electric propulsion is presented to ensure a property of robustness against rotor failure from the control perspective. Based on the concept of null controllability, a quality measure is derived to evaluate and quantify the performance of a given design with the consideration of rotor failure. An optimization problem whose cost function is based on the quality measure is formulated and its optimal solution identifies a set of optimal design parameters that maximizes an aircraft’s ability to control its attitude and hence its position. The effectiveness of the proposed design procedure is validated through the results of experimentation with the Autonomous Flying Ambulance model being developed at Caltech’s Center for Autonomous Systems and Technologies

Security governance and the private military industry in Europe and North America

Even before Iraq the growing use of private military contractors has been widely discussed in the academic and public literature. However, the reasons for this proliferation of private military companies and its implications are frequently generalized due to a lack of suitable theoretical approaches for the analysis of private means of violence in contemporary security. As a consequence, this article contends, the analysis of the growth of the private military industry typically conflates two separate developments: the failure of some developing states to provide for their national security and the privatisation of military services in industrialized nations in Europe and North America. This article focuses on the latter and argues that the concept of security governance can be used as a theoretical framework for understanding the distinct development, problems and solutions for the governance of the private military industry in developed countries.The United States Institute of Peace and the German Academic Exchange Service