Open Research Position: Data Science / Machine Learning for Design

Location: Cambridge MA (remote option is possible but must have a US work visa/authorization)
Position Type: Part-time, Temporary
Compensation: part-time 10 – 20 hours/week, hourly rate dependent on experience.
Duration: Fall 2024
Job Description:
We are seeking a highly motivated and talented graduate student with expertise in Data Science and Machine Learning to join our research team for a short-term research project. The primary focus of this position is to develop predictive models that can forecast preferences and ratings based on image data, in the context of an on-going design study on the aesthetic perception of wall and floor tiles. This role will provide an excellent opportunity to apply advanced machine learning techniques to a practical problem while contributing to cutting-edge research. This work is part of the Laboratory of Design Technologies and the Material Processes and Systems Group at the Harvard Graduate School of Design.
Key Responsibilities:
• Model Development: Design and implement machine learning models to predict user preferences and ratings from image data.
• Data Processing: Clean, preprocess, and augment mid-size datasets of images to prepare them for model training and evaluation.
• Model Training and Evaluation: Train, validate, and tune models to ensure high accuracy and robustness. Conduct performance evaluations using appropriate metrics.
• Research Documentation: Document methodologies, experiments, and results in a clear and concise manner for both internal use and potential publication.
• Collaboration: Work closely with interdisciplinary team members including designers, architects, industry experts, and supervisors to refine models and achieve research goals.
• Literature Review: Stay updated with recent advancements and trends in machine learning and related fields to incorporate best practices into the project.
Required Qualifications:
• Education: Currently enrolled in, or recent graduate of a graduate program (Master’s or Ph.D.) in Data Science, Computer Science, Machine Learning, or a closely related field.
• Technical Skills:
o Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Keras.
o Strong programming skills in Python.
• Analytical Skills: Strong understanding of statistical and machine learning algorithms, including supervised and unsupervised techniques.
• Research Experience: Proven experience in conducting research projects, with a strong emphasis on machine learning or data science.
• Problem-Solving: Strong analytical and problem-solving skills with the ability to work independently and in a team environment.

Preferred Qualifications:
• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with computer vision techniques and libraries such as OpenCV, scikit-image, or similar.
• Publications or significant coursework in machine learning, computer vision, or related areas.
• Familiarity with data visualization tools and techniques.
Application Process:
Interested candidates should submit the following documents:
1. Resume/CV: Detailing relevant educational background and research experience.
2. Statement: Explaining your interest in the position and highlighting any specific expertise that aligns with the job description. Max. 250 words.
3. References: Contact information for at least one academic or professional reference.
Please send your application materials to [email protected] by September 15th 2024.

LDT Industry Advisors Kick-Off Meeting

We are looking forward to hosting our first in person meeting with the LDT Industry Advisors, kicking off the next phase of research and engagement! We are eager to start working on new ideas and prototypes for a better built environment! This year we will begin with a summer research studio that includes current students in the Master in Design Engineering Program at Harvard, and we will interact frequently with our industry advisors. The goal for the summer is to map out the space of interest, research precedents, and generate ideas for research agendas that will then be pursued during the remainder of the year! Our theme will be ‘Artificial Intelligence, Internet of Things, and the Build Environment’, and we will focus on the threefold aspects of data, materials, and the human experience.