Hrs2025 / 040 Investigador / Researcher

Universidad Politécnica de Madrid Employees, Location, Alumni; Madrid; Presencial; EUR 30.000 - 60.000; Jornada completa

Descripción de la vacante

Una institución académica de renombre busca un investigador de primera etapa apasionado por la inteligencia artificial y la ciberseguridad. En esta emocionante oportunidad, serás responsable del desarrollo de modelos innovadores que analicen el comportamiento del usuario y detecten amenazas internas. Trabajarás con tecnologías avanzadas y herramientas de aprendizaje automático, integrando tus modelos en sistemas complejos que evalúan riesgos en tiempo real. Si tienes un fuerte trasfondo en programación y un interés por la seguridad cibernética, esta posición te permitirá contribuir a proyectos significativos y avanzar en tu carrera en un entorno colaborativo y dinámico.

Servicios

Cursos de formación

Asistencia a conferencias

Formación

• Experiencia en el desarrollo de modelos de aprendizaje supervisado y no supervisado.
• Conocimiento de amenazas INSIDER y uso de la matriz MITRE ATT&CK.
• Capacidad para trabajar con registros de sistemas y extraer información significativa.

Responsabilidades

• Desarrollo de modelos de inteligencia artificial basados en actividades de usuario.
• Modelado de actividad del usuario para identificar amenazas INSIDER potenciales.
• Integración de modelos en un sistema complejo para evaluar riesgos.

Conocimientos

Desarrollo de modelos de aprendizaje supervisado

Desarrollo de modelos de aprendizaje no supervisado

Análisis de amenazas INSIDER

Uso de la matriz MITRE ATT&CK

Interacción con registros de sistemas (Windows, UNIX, MacOS)

Detección de anomalías

Técnicas de aprendizaje en línea

Programación en Python

Programación en Java

Uso de herramientas de scripting (Bash, PowerShell)

Educación

Título de Bachelor o equivalente

Herramientas

Kafka

Spark Streaming

Airflow

ELK Stack (Elasticsearch, Logstash, Kibana)

TensorFlow

Scikit-learn

Keras

Descripción del empleo

Organisation / Company: UNIVERSIDAD POLITECNICA DE MADRID

Department: HRS4R

Researcher Profile: First Stage Researcher (R1)

Positions: Bachelor Positions

Country: Spain

Application Deadline: 30 Jan 2025 - 20:00 (Europe / Madrid)

Type of Contract: Temporary

Job Status: Full-time

Offer Starting Date: 15 Feb 2025

Is the job funded through the EU Research Framework Programme? Not funded by a EU programme

Is the Job related to staff position within a Research Infrastructure? No

Offer Description

• Development of artificial intelligence models based on user activities, taking into account log collection agents from systems (Windows / UNIX / MacOS).
• Parameterization of INSIDER cybersecurity attacks based on the MITRE ATT&CK matrix, where Techniques, Tactics, and Procedures must be identified.
• Modeling user activity to identify potential INSIDER threats.
• Development of user session modeling, using clustering algorithms based on unsupervised learning.
• Integration of the developed models into a complex system that allows characterizing INSIDER threats through real-time learning techniques (online learning) and assessing the system's risk based on the previously defined characteristics.

Where to apply

E-mail: Research Field

Minimum Qualifications

Bachelor Degree or equivalent

Skills / Qualifications

• Expertise in developing models using both supervised and unsupervised learning, particularly with clustering algorithms for user activity modeling.
• Strong understanding of INSIDER threats, with experience in using the MITRE ATT&CK matrix to identify Techniques, Tactics, and Procedures (TTPs).
• Ability to work with system logs from platforms like Windows and UNIX / MacOS, extracting meaningful insights to track user behavior.
• Proficiency in languages such as Python, Java, and scripting tools (e.g., Bash, PowerShell) for system interaction and model development.
• Skill in applying anomaly detection algorithms to recognize unusual patterns that may signal insider threats.
• Experience with online learning techniques to enable the integration of models into systems that assess risks and evolve in real-time.

Specific Requirements

• Experience with real-time data processing systems, such as Kafka, Spark Streaming, or Airflow.
• Experience in developing anomaly detection models based on behavioral analysis.
• Familiarity with tools such as ELK Stack (Elasticsearch, Logstash, and Kibana).
• Proficiency with the MITRE ATT&CK framework and the ability to map threats to Techniques, Tactics, and Procedures (TTPs).
• Familiarity with unsupervised learning methods and experience with real-time learning (online learning).
• Experience with Python and popular AI / ML libraries such as TensorFlow, Scikit-learn, and Keras.

Languages

Additional Information

Training courses and attendance at conferences.