Job offer

Universidad Politecnica De
Municipality of Cartagena, Spain
2 days ago

Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
€ 13K

Job location

Remote
Municipality of Cartagena, Spain

Tech stack

Artificial Intelligence
Airflow
Data analysis
Big Data
Computer Programming
Computer Engineering
Information Engineering
Python
KNIME
Machine Learning
NoSQL
Open Source Technology
Software Engineering
Data Streaming
Automated Information System (AIS)
Data Processing
Information Technology
Modeling and Simulation
Machine Learning Operations
Docker

Requirements

PROFESSIONAL CATEGORY: GROUP I. Holders of an advanced degree (Bachelor's degree, Master's degree, Professional Engineer, Architect, or equivalent).

REQUIRED QUALIFICATION: Bachelor's degree, undergraduate degree, engineering degree, or master's degree in Computer Engineering, Mathematics, Data Science or Data Engineering, Statistics, Physics, or related fields in the sciences and engineering.

In the case of degrees obtained abroad (including EU degrees), candidates must provide proof of the corresponding validation or, where applicable, the credential attesting to the equivalence.

In accordance with the provisions of the Law on Science, Technology, and

Innovation, if the required academic degree is not held, applications may be accepted from candidates who possess training and experience commensurate with the tasks to be performed and the merits to be evaluated:

  • Training courses and/or courses from official university degrees related to programming, data processing, and machine learning.

  • Professional experience in Python development, data flow automation, and data modeling/analysis., Academic Background (20%): The academic record for the required degrees will be evaluated.

Specific Training (15%): Specialized training related to the position: a master's or postgraduate degree in data science, AI, or machine learning; accredited courses in Python, data processing, simulation, or MLOps.

Professional experience (35%): Python programming on real-world projects; design and automation of data flows (KNIME or equivalents: Airflow, Docker, relational and NoSQL databases); modeling and simulation, time series, and applied machine learning; processing of AIS, maritime, transportation, or energy data and/or big data; and participation in R&D&I activities or collaboration with universities/research centers.

Languages (5%): Certified proficiency in English, due to its relevance for technical documentation and the international dissemination of results.

Other merits (5%): Relevant professional certifications (cloud, data, etc.); software development and contributions of open-source code or data (public repositories, Zenodo); outreach activities; teaching or scientific communication experience.

Personal interview (20%): Interview to assess suitability for the position: technical proficiency (simulation, time series, data streams, AIS/big data), ability to work independently within a research team, and communication skills. May include a practical programming/data analysis test. Same format and treatment for all candidates., Research Field Computer science » Database management

Education Level Bachelor Degree or equivalent

Research Field Computer science » Database management

Benefits & conditions

WEEKLY DEDICATION: The position will be partial, and the workweek will be 15 hours, carried out from Monday to Friday.

GROSS ANNUAL REMUNERATION: The employee will receive an annual gross salary of 13.267,94 euros.

PROJECT TITLE: Decarbonization and improvement of energy efficiency in the Spanish shipping fleet.

DURATION: The term of this contract will be contingent upon the availability of funds for the aforementioned research line.

Current R&D&I activity:

"Decarbonization and Improvement of Energy Efficiency in the Spanish Maritime Fleet," reference PID2024-160978OB-I00, funded by MICIU/AEI/10.13039/501100011033 and by the ERDF, EU. Budget line 30.05.18.9950 541A 642.10 (code: 2025/00329/001).

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