Research Engineer - Artificial intelligence, Machine Learning and signal processing

Research Engineer - Artificial intelligence, Machine Learning and signal processing

Job Reference: RRP.12.31.14.4

Employer: International Iberian Nanotechnology Laboratory (INL)

Location: Braga, Portugal

Group/Unit: M. Martins Research Group

Number of Vacancies: 1

Employment Type: Full time

Contract Duration: 13 months

Open Date for Applications: October 2nd, 2024

Closing Date for Applications: October 22nd, 2024, 23h00m (Lisbon Time)

Key words: #ArtificialIntelligence #MachineLearning #DeepLearning #SupervisedLearning #ReinforcementLearning #ArtificialNeuralNetworks #SupportvectorMachines #BayesianNetworks

Overview

The M. Martins Research Group is expected to function as a cohesive, multifaceted engineering team that promotes the INL’s core R&D&I skills, in particular in the area of system engineering. It aims to expand the installed capacities for an interdisciplinary approach to transform concepts into high quality nanotechnology-based products and services.

The objective is to create a multidisciplinary team of Engineers from different areas, namely Mechanical, Electric, Physics, Computer Science, and Machine Learning, to work very closely with each other and that will ensure continuity between the knowledge accumulated at INL and the existing knowledge in companies, enabling a faster and more effective knowledge transfer. Each member will bring their contribution to the team to maximise the construction of very complex systems capable of responding to crosscutting needs of the companies with which they will be working.

We are looking for a Research Engineer to join our group in the Stationary batteries for renewable energy self-consumption of small to-medium size facilities and Batteries as the key elements in virtual power plants project of the NGS Agenda; the Batteries as the key elements in virtual power plants project of the Bioeconomia Azul Agenda; the Sensors for presence detection project of the ILLIANCE Agenda and, the Portable SERS platform for antibiotic residues detection project of the Smartgnostic Agenda, under the PRR framework.

Job Duties

The Research Engineer will be responsible for designing and building systems and interfaces in several areas of application and will undertake the following main activities and responsibilities:

• Model, build, and test AI software to ensure it can take on large swaths of data and achieve desired results;
• Analyse and interpret data time signals, images, time series, etc;
• Design and develop AI models from scratch;
• Find patterns and anomalies within large datasets in supervised and preferably unsupervised methods;
• Design, build and manage ML software applications;
• Experimentation and Prototyping;
• Use Python, JavaScript, and C++ to create a faster, more capable AI;
• Analyse statistics, data, and algorithms for projection accuracy;
• Stay current on AI knowledge, trends, and regulations;
• Ethical considerations and responsible AI practices;
• Collaborate and communicate within an interdisciplinary team.

Mandatory Qualifications

Education

• MSc in Artificial Intelligence, Machine Learning, Data Science, Computer Engineering, Computer Science or any other related field.

Experience

• At least professional experience of 1 years in the industry field.

Technical Skills

• Programming Languages
  • Python, including libraries such as TensorFlow, PyTorch, scikit-learn, and Keras;
  • JavaScript, including frontend development and integration with Node.js frameworks;
  • C++ for performance-critical AI tasks.

• Machine Learning and Deep Learning
  • Strong understanding of machine learning concepts, algorithms, and techniques, including supervised learning, unsupervised learning, reinforcement learning, and deep learning;
  • Experience with popular deep learning frameworks such as TensorFlow, PyTorch, and Keras for building and training neural networks;
  • Experience in analysing and interpreting data collected by different sensors such as signals, images, time series, etc.;
  • Experience in adapting developed models to bare metal platforms;
  • Knowledge of basic algorithms, object-oriented and functional design principles, and best-practice patterns;
  • Familiarity with advanced topics in deep learning, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and transformer models.

• Data Analysis and Visualisation
  • Proficiency in data analysis and manipulation using libraries like Pandas and NumPy;
  • Experience with data visualisation tools such as Matplotlib, Seaborn, and Plotly for creating insightful visualizations of complex datasets;
  • Natural Language Processing (NLP).

• Computer Vision
  • Understanding of computer vision algorithms and frameworks, including OpenCV, TensorFlow Object Detection API, and PyTorch Vision for tasks such as image classification, object detection, image segmentation, and facial recognition.

• Model Evaluation and Optimisation
  • Proficiency in evaluating and optimising machine learning models using techniques such as cross-validation, hyperparameter tuning, regularisation, and ensemble methods to improve model performance and generalisation.

• Software Engineering Practices:
  • Knowledge of software engineering principles and best practices, including version control systems (e.g., Git), software design patterns, unit testing, and continuous integration/continuous deployment (CI/CD) pipelines.

Personal Skills

• Strong motivation to work both independently and as part of a team in an interdisciplinary environment, with the ability to pay close attention to detail and to meet deadlines.
• Excellent communication skills.
• Capable of establishing collaborative ties.
• Team work spirit.

Our Benefits

• Competitive salary;
• Tax benefits and other Diplomatic privileges;
• Private health insurance;
• Family allowances (according to family situation);
• Free nursery service at INL premises (subject to availability);
• Support for education fees of dependent children;
• Relocation support;
• 30 working days of annual leave.

How to Apply

The application must be in English and include the following mandatory documents:

a)     Cover letter;

b)     Curriculum Vitae;

c)      Academic and/or Professional diplomas;

d)     Recognition of academic degrees (only academic degrees awarded by non-Portuguese higher education institutions) *

*The selected candidate(s) with an academic degree granted by a non-Portuguese higher education institution must present, for hiring purposes, the certificate of recognition of that degree(s), issued by the Portuguese Directorate General for Higher Education or by a Portuguese Public Higher Education Institution. Please consult the website of the Portuguese Directorate General for Higher Education: https://www.dges.gov.pt/en.

Online application instructions:

1. The application is made online by clicking the “Apply” button;
2. The candidate must complete all required sections of the online application form;
3. The candidate must submit the mandatory documents mentioned above in pdf format by including them in the “Additional files” section using the “Add portfolio” button.

Important note:

Incomplete applications including the failure to provide mandatory documents or providing inaccurate information will result in the application not being considered.

How the Selection Process works
 

A. Applications eligibility check

This stage will be carried out on the basis of the mandatory requirements, education, experience and technical skills defined for the job, as well as the validation of the mandatory documents. Only candidates who meet the eligibility criteria will move forward to the next stage.

B. CV Assessment

The Selection Committee will evaluate the eligible applications based on their CV and other submitted documents and the suitability for the position. The best ranked candidates will be shortlisted for the interview stage(s).

C. Interview(s)

The interview(s) may be done in different formats: video recording, online or onsite.

The question based interview will evaluate the match between the candidate’s profile and the requirements for the position, including the technical and personal skills. To better support this stage, the candidate may be requested to prepare a short presentation.

D. Nomination

The selected candidate will be nominated and formally offered the position, including the disclosure of the contractual conditions. 

Additional Information

Application feedback

We highly value your interest in becoming part of the INL experience and it is important for us to maintain good communications with all candidates. No matter the outcome of your application, we will always provide you with feedback.

Equal Opportunity and Non-Discrimination Principle

INL follows a non-discrimination and equal access principle, wherefore no candidate can be privileged, benefited, impaired or deprived of any rights whatsoever, or be exempt of and duties based on any possible discriminatory issues.

The advertisement deadline may be extended at any time without previous notice in order to improve the suitability and effectiveness of the recruitment process.

About INL

The International Iberian Nanotechnology Laboratory – INL (http://www.inl.int), is the first and only Intergovernmental Organisation in the world entirely focused on Nanoscience and Nanotechnology.

It was founded under an international legal framework to perform interdisciplinary research, deploy and communicate nanotechnology for the benefit of society. INL aims to be a recognised leading global nanotechnology innovation hub.