📍 Job Overview

Job Title: Doctoral Researcher in Sustainable AI and Cloud Computing
Company: Aalto University
Location: Otaniemi, Espoo, Finland
Job Type: Full-Time (Hybrid)
Category: Research, AI, Cloud Computing
Date Posted: 2025-07-02
Experience Level: Entry to Mid (0-2 years)
Remote Status: On-site with hybrid flexibility

🚀 Role Summary

Key Responsibilities: Conduct research on sustainable AI and cloud computing, focusing on reducing the environmental impact of AI throughout its lifecycle.
Key Skills: AI, Machine Learning, Cloud Computing, Programming, Networking Technologies, Energy Systems, Sustainability, Statistical Analysis, Optimization Techniques.
Key Technologies: AI frameworks, cloud platforms, programming languages (Python, etc.), energy metrics, carbon metrics.

📝 Enhancement Note: This role requires a strong background in AI and machine learning, with a focus on sustainability and environmental impact assessment. Candidates should be comfortable working with various AI architectures, training models, and applying them to different tasks.

💻 Primary Responsibilities

Research & Development: Identify and evaluate carbon metrics, empirically evaluate AI lifecycle stages, and develop methodologies to estimate long-term environmental impact.
Software Development: Build a software framework to quantify the long-term environmental impact of AI and cloud computing.
Collaboration: Work closely with the team, collaboration partners, and leading experts in the field to advance research and optimize AI's environmental footprint.
Communication: Effectively communicate research findings, present at conferences, and publish in relevant journals.

📝 Enhancement Note: This role involves interdisciplinary research, requiring candidates to collaborate with various teams and adapt to different research environments.

🎓 Skills & Qualifications

Education:

Master's degree in Computer Science, Communications Engineering, or a related field (with a CGPA of at least 3/5)
Proficiency in English (see required language proficiency)

Experience:

Experience in AI and machine learning, including understanding of various DNN architectures, training models, and applying them for different tasks
Good programming skills (sample code required during recruitment)

Required Skills:

Strong interest and motivation in improving the sustainability of networked systems
Good programming skills (sample code required during recruitment)
Experience in AI and machine learning
Familiarity with cloud computing and networking technologies
Knowledge of energy systems, electricity markets, and carbon metrics

Preferred Skills:

Experience in energy systems and environmental impact assessment
Familiarity with optimization techniques and statistical analysis
Experience working in an interdisciplinary research environment

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

A CV highlighting relevant experience and skills
A short letter of motivation (max. 1 page) detailing your interest and motivation for the role
Sample code, preferably on a code repository, demonstrating your programming skills and role in developing the software
Transcripts of grades from Bachelor’s and Master’s degrees

Technical Documentation:

Names and email addresses of two reference providers
A 1-page research plan detailing specific research questions (submitted after a preliminary interview)

📝 Enhancement Note: While a web portfolio in the traditional sense is not required for this role, candidates should be prepared to demonstrate their programming skills and provide a sample of their code during the recruitment process.

💵 Compensation & Benefits

Salary Range: The position offers a competitive salary of approximately 3000 EUR/month.

Benefits:

Comprehensive occupational health benefits
Membership in Finland’s social security system

Working Hours: Full-time position with a 40-hour workweek, flexible working arrangements, and opportunities for research visits.

📝 Enhancement Note: The salary range is based on Aalto University's standard doctoral researcher salary and is subject to the university's salary scales and collective agreements.

🎯 Team & Company Context

Company Culture:

Aalto University is a multidisciplinary community where science and art meet technology and business, fostering research breakthroughs and innovative solutions to global challenges.
The university values diversity and inclusivity, with a community made up of 120 nationalities, 14,000 students, 400 professors, and 5,000 faculty and staff.
The School of Electrical Engineering offers a vibrant and collaborative environment, with a focus on advancing research in networked systems and sustainability.

Team Structure:

The Cloud and Network Computing group, headed by Assistant Professor Gopika Premsankar, is dedicated to advancing research in networked systems, focusing on lowering the environmental footprint while enhancing sustainability, performance, and reliability.
The team works closely with collaboration partners within Finland and internationally in the USA, Netherlands, and Germany, offering opportunities for research visits to strengthen collaboration.

Development Methodology:

The team employs optimization techniques, applied machine learning, and statistical analysis to achieve its research objectives.
The DecAI project aims to develop a framework to estimate carbon emissions across AI's development, operation, and use, and to optimize AI's serving operations through carbon-efficient algorithms.

Company Website: Aalto University

📝 Enhancement Note: Aalto University provides a vibrant and collaborative environment, with a strong focus on research and innovation. The Cloud and Network Computing group offers a unique opportunity to work on cutting-edge research in sustainable AI and cloud computing.

📈 Career & Growth Analysis

Web Technology Career Level: Doctoral Researcher (4-year contract)

Reporting Structure: The doctoral researcher will report directly to Assistant Professor Gopika Premsankar and work closely with the team, collaboration partners, and leading experts in the field.

Technical Impact: The role involves conducting independent research, publishing findings in relevant journals, and presenting at conferences. The research aims to have a significant impact on reducing the environmental footprint of AI and cloud computing.

Growth Opportunities:

Opportunities for research visits to strengthen collaboration with leading experts in the field
Potential for postdoctoral research positions or academic career paths after completing the doctoral program
Development of expertise in AI, cloud computing, networking technologies, energy systems, and sustainability

📝 Enhancement Note: This role offers significant growth opportunities, allowing candidates to develop their research skills, gain experience working in an interdisciplinary environment, and build a strong portfolio for their academic career.

🌐 Work Environment

Office Type: The primary workplace is Otaniemi, Espoo, with a hybrid working arrangement offering flexibility for remote work.

Office Location(s): Otaniemi, Espoo, Finland

Workspace Context:

The Otaniemi campus is a thriving and connected community of 100 nationalities, 13,000 students, and 4,500 employees.
The campus offers amazing architecture, calming nature, a variety of cafes, restaurants, services, and good transport connections.

Work Schedule: Full-time position with a 40-hour workweek, flexible working arrangements, and opportunities for research visits.

📝 Enhancement Note: Aalto University provides a vibrant and collaborative work environment, with a strong focus on research and innovation. The hybrid working arrangement offers flexibility for remote work while maintaining a strong on-campus presence.

📄 Application & Technical Interview Process

Interview Process:

Preliminary interview to assess the candidate's research background, motivation, and fit for the role.
Submission of a 1-page research plan detailing specific research questions (after the preliminary interview).
Final evaluation and hiring decision based on the research plan and overall fit for the role.

Portfolio Review Tips:

Highlight relevant research experience and skills in your CV and letter of motivation.
Provide a sample of your code demonstrating your programming skills and role in developing the software.
Tailor your research plan to the DecAI project, addressing specific research questions and outlining your approach to reducing AI's environmental impact.

Technical Challenge Preparation:

Brush up on your AI and machine learning skills, focusing on various DNN architectures, training models, and applying them to different tasks.
Familiarize yourself with cloud computing, networking technologies, energy systems, and carbon metrics.
Prepare for questions related to optimization techniques, statistical analysis, and interdisciplinary research.

ATS Keywords: (Categorized for better readability)

Programming Languages:

Python, R, MATLAB, etc.

AI & Machine Learning:

Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Computer Vision, Reinforcement Learning, etc.

Cloud Computing & Infrastructure:

Cloud Computing, Infrastructure as Code, Containerization, Virtualization, Serverless Architecture, etc.

Networking Technologies:

Networking, Network Protocols, Network Architecture, Network Security, etc.

Energy Systems & Carbon Metrics:

Energy Systems, Electricity Markets, Carbon Metrics, Environmental Impact Assessment, etc.

Tools & Methodologies:

Optimization Techniques, Statistical Analysis, Data Analysis, Data Visualization, etc.

Soft Skills:

Problem-Solving, Critical Thinking, Communication, Collaboration, Teamwork, etc.

Industry Terms:

Sustainability, Environmental Impact, Carbon Footprint, AI Lifecycle, Cloud Computing, etc.

📝 Enhancement Note: The interview process for this role is highly competitive, with a strong focus on research background, motivation, and fit for the role. Candidates should be prepared to demonstrate their programming skills, provide a sample of their code, and submit a 1-page research plan outlining their specific research questions and approach to reducing AI's environmental impact.

🛠 Technology Stack & Web Infrastructure

AI & Machine Learning Technologies:

TensorFlow, PyTorch, Keras, Scikit-learn, etc.
Cloud AutoML, Auto-sklearn, H2O.ai, etc. (for automated machine learning)

Cloud Computing & Infrastructure:

AWS, Google Cloud, Microsoft Azure, etc.
Docker, Kubernetes, Terraform, etc. (for containerization and infrastructure as code)
Serverless architecture (e.g., AWS Lambda, Google Cloud Functions)

Networking Technologies:

TCP/IP, UDP, DNS, etc.
Network protocols (e.g., HTTP, HTTPS, MQTT)
Network architecture (e.g., client-server, peer-to-peer)
Network security (e.g., encryption, authentication, firewalls)

Energy Systems & Carbon Metrics:

Energy metrics (e.g., power consumption, energy efficiency)
Carbon metrics (e.g., carbon emissions, carbon footprint)
Environmental impact assessment tools (e.g., LCA, Life Cycle Assessment)

📝 Enhancement Note: The technology stack for this role is highly specialized, focusing on AI, machine learning, cloud computing, networking technologies, energy systems, and carbon metrics. Candidates should be comfortable working with various AI architectures, training models, and applying them to different tasks, as well as familiar with cloud platforms, networking protocols, and energy systems.

👥 Team Culture & Values

Web Development Values:

Sustainability: A strong commitment to reducing the environmental impact of AI and cloud computing.
Innovation: Encouraging creative problem-solving and continuous learning to advance research in sustainable AI and cloud computing.
Collaboration: Working closely with the team, collaboration partners, and leading experts in the field to achieve research objectives.
Excellence: Pursuing high-quality research, publishing findings in relevant journals, and presenting at conferences.

Collaboration Style:

The team employs a collaborative approach, working closely with each other, collaboration partners, and leading experts in the field.
The team values open communication, active listening, and constructive feedback to foster a positive and productive work environment.
The team encourages knowledge sharing, technical mentoring, and continuous learning to support the professional development of its members.

📝 Enhancement Note: The team culture for this role is highly collaborative, with a strong focus on research, innovation, and sustainability. The team values open communication, active listening, and constructive feedback to foster a positive and productive work environment.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Identifying and evaluating carbon metrics for reducing the environmental impact of AI and cloud computing.
Empirically evaluating different parts of the AI lifecycle, including development (training), operation (inference), and use.
Developing methodologies to estimate the long-term impact of AI on carbon emissions and other environmental indicators.
Building a software framework to quantify the long-term environmental impact of AI and cloud computing.

Learning & Development Opportunities:

Developing expertise in AI, cloud computing, networking technologies, energy systems, and sustainability.
Attending conferences, workshops, and training sessions to enhance research skills and stay up-to-date with industry trends.
Collaborating with leading experts in the field to gain insights and perspectives on sustainable AI and cloud computing.
Pursuing postdoctoral research positions or academic career paths after completing the doctoral program.

📝 Enhancement Note: This role offers significant technical challenges and learning opportunities, allowing candidates to develop their research skills, gain experience working in an interdisciplinary environment, and build a strong portfolio for their academic career.

💡 Interview Preparation

Technical Questions:

AI & Machine Learning: Can you describe your experience with various DNN architectures, training models, and applying them to different tasks? How have you optimized AI models for performance and sustainability?
Cloud Computing: How familiar are you with cloud platforms, containerization, and infrastructure as code? Can you discuss a project where you optimized cloud resources for sustainability?
Networking Technologies: Can you explain your understanding of networking protocols, network architecture, and network security? How have you applied these concepts in a project?
Energy Systems & Carbon Metrics: How do you approach evaluating energy consumption and carbon emissions in AI and cloud computing? Can you discuss a project where you assessed and optimized the environmental impact of AI or cloud computing?

Company & Culture Questions:

Research Focus: How do you see your research contributing to the DecAI project and the broader goal of reducing AI's environmental impact?
Collaboration: How do you approach working in an interdisciplinary research environment, and how do you ensure effective communication and collaboration with team members and external partners?
Career Development: How do you plan to develop your research skills and expertise in sustainable AI and cloud computing throughout your doctoral program?

Portfolio Presentation Strategy:

Research Plan: Tailor your research plan to the DecAI project, addressing specific research questions and outlining your approach to reducing AI's environmental impact.
Code Sample: Provide a sample of your code demonstrating your programming skills and role in developing the software.
Portfolio Essentials: Highlight relevant research experience and skills in your CV and letter of motivation.
Communication: Prepare for questions related to your research background, motivation, and fit for the role, as well as your approach to reducing AI's environmental impact.

📝 Enhancement Note: The interview process for this role is highly competitive, with a strong focus on research background, motivation, and fit for the role. Candidates should be prepared to demonstrate their programming skills, provide a sample of their code, and submit a 1-page research plan outlining their specific research questions and approach to reducing AI's environmental impact.

📌 Application Steps

To apply for this Doctoral Researcher position in Sustainable AI and Cloud Computing:

Prepare a CV highlighting your relevant experience and skills.
Write a short letter of motivation (max. 1 page) detailing your interest and motivation for the role.
Provide a sample of your code, preferably on a code repository, demonstrating your programming skills and role in developing the software.
Gather the names and email addresses of two reference providers.
Submit your application materials through the Aalto University recruitment site ("Apply now!") by October 31st, 2025.
After a preliminary interview, submit a 1-page research plan detailing specific research questions (if requested).

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web technology industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Doctoral Researcher in sustainable AI and cloud computing