Inria has one of its five priority focuses on artificial intelligence, automatic learning, and related subjects. Recent results in these areas have created crucial opportunities, but at the same time, imply significant challenges. Within this context, issues such as causality inference, explainability of AI models, and ethical issues have gained central space.
At Inria Chile, we seek to develop these directions and, in turn, apply these principles in projects related to marine ecology, climate change mitigation, accident prevention, precision agriculture, mining, transportation, health, astronomy, among others.
Identificación del cargo
|Number of positions||:||1|
|Workplace||:||Inria Chile offices (*telework mode until further notice)|
|Direct supervisor's position||:||Scientific Director|
|Duration||:||3 months trial with a permanent contract in case of successful completion of the missions entrusted.|
|Salary||:||2,400,000 CLP / month (before taxes)|
Objectives and Functions of the Position
The postdoc will be a member of Inria Chile's R & D team and will implement the center's machine learning models.
The functions of the position are:
- Creation and optimization of models using machine learning techniques.
- To develop a state of the art methods related to causality inference and explainable AI.
- Improvement of data collection procedures to include relevant information for the creation of analytical systems.
- Attract R&D funds with industry and academia.
- Make ad-hoc analysis, visualize, and precisely report results.
- Co-develop software with Inria project teams.
- Participate in a network of development experts within the center and/or at the national and international levels.
- Create training courses, sharing of technology watch knowledge, tools, or recommended development methods.
- Provide technical mentorship to junior or interns engineers as part of the technological development actions.
- Produce reports, scientific articles, and minutes as required, in collaboration with Inria Chile team members.
- Participate in dissemination actions such as courses, conferences, lectures, among other activities.
- Ph.D. in computer science, computer science, engineering, statistics, applied mathematics, and related careers
- Possess publications in the area in renowned media.
- Have autonomy and leadership in organizing R+D projects and attract funds.
- Native or advanced English. French desirable.
- Be capable of find solutions to poorly defined problems by taking advantage of pattern detection on potentially large data sets.
- Have an excellent understanding of basic machine learning techniques and algorithms.
- Knowledge in neural networks, deep learning, convolutional and recurrent networks.
- Learning by reinforcement, active learning, transfer learning.
- Know essential natural language processing tools.
- Have skills in applied statistics, design of experiments, distributions, hypothesis testing, among others.
- Machine learning development stack (scikit-learn, Tensorflow/PyTorch, Jupyter, Spark )
- Methodologies: Scrum, Test Driven Development, Continuous Integration.
- Experience in maintaining an open-source project with packaging, regular releases in standard distribution channels, and problem tracking.
- Coordination and project management skills
Be autonomous, curious, and enjoy teamwork.
Quality of work.
Organization and planning of tasks.
Benefits and advantages
> To be part of an institution of excellence and international recognition
> 13th salary
> Complementary health insurance
> 5 additional vacation days
> Incentives for voluntary social security savings
Two letters of recommendation