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.

Future Strategies Keynote

Prof. Martin Bechthold was honored to deliver a keynote lecture at the Future Strategy Symposium, celebrating the 10-year anniversary of the Graduate School of Future Strategy at the Korea Advanced Institute of Science & Technology (KAIST).

MaP+S Research @ DigitalFUTURES !

MaP+S would like to invite you to join us for an exciting research livestream hosted by Digital Futures !

Whether you are an expert in the field or simply interested in learning more about our research, we would love to have you join us for this engaging and informative event.

The livestream will take place here on 29th April, 10 am EDT.

We hope to see you there! Don’t forget to mark your calendars and spread the word to anyone who may be interested.

Recording to his can be found here : Link

Katarina Richter-Lunn (MDes ’21) awarded a 2022 Paul & Daisy Soros Fellowship

Courtesy of Katarina Richter-Lunn

Harvard University Graduate School of Design DDes candidate Katarina Richter-Lunn (MDes ’21) has been awarded the 2022 Paul & Daisy Soros Fellowship for New Americans, a merit-based graduate school program for 30 immigrants and children of immigrants. Chosen from a competitive pool of over 1,800 applicants, Richter-Lunn was selected for her potential to make significant contributions through her research and work in the United States. She will join 10 other Harvard affiliated students who are being honored in 2022 by the Soros organization—all of whom receive up to $90,000 to support graduate studies.

More info here.