Required PhD Machine Learning Research Intern
27984
Role Description
About the team: The internship is open for PhD students in a machine learning related field like Planning with LLMs, Multilingual Training Adaptation, Recommender System and Ranking, Bidding, Synthetic Data Generation, Entity Representation Learning, Reinforcement learning and Classification.
Applicants are asked to attach with their CV the email address of their supervisor or co-supervisor. This email will be used to ask for a recommendation letter at a later date.
Please complete your application before March 31st, 2026. Participation in the internship program requires that you are located in Israel for the duration of the internship program (3 months)
Role Description:
As a Machine Learning Research intern at Booking.com in Tel-Aviv, you will have the opportunity to tackle real world problems by pushing the boundaries of the state-of-the-art, with the goal of publishing your work.
You will join us for a 3-month internship (preferred start date: May) focused on Data-Centric AI. In this project, you will tackle the "glass ceiling" of NLU performance: inherent ambiguity in annotation guidelines and label taxonomies. You will move beyond traditional noise reduction to investigate why human annotators disagree and how these disagreements corrupt "ground truth," directly influencing how we evaluate and improve state-of-the-art models.
Key Job Responsibilities and Duties:
Survey the Landscape: Conduct a comprehensive literature review to synthesize current approaches to data ambiguity, identifying the strengths and limitations of existing methods in handling label noise and taxonomy gaps.
Innovate & Design: Devise novel techniques and metrics to detect, quantify, and resolve inherent ambiguities within NLP datasets and annotation guidelines.
Experiment & Validate: Design and execute rigorous experiments to evaluate your proposed methods, measuring their impact on model reliability and ground truth accuracy.
Publish Findings: Summarize your conclusions and contribute to writing a research paper with the aim of submitting to a top-tier NLP conference (e.g., ACL, EMNLP).
27984
Role Description
About the team: The internship is open for PhD students in a machine learning related field like Planning with LLMs, Multilingual Training Adaptation, Recommender System and Ranking, Bidding, Synthetic Data Generation, Entity Representation Learning, Reinforcement learning and Classification.
Applicants are asked to attach with their CV the email address of their supervisor or co-supervisor. This email will be used to ask for a recommendation letter at a later date.
Please complete your application before March 31st, 2026. Participation in the internship program requires that you are located in Israel for the duration of the internship program (3 months)
Role Description:
As a Machine Learning Research intern at Booking.com in Tel-Aviv, you will have the opportunity to tackle real world problems by pushing the boundaries of the state-of-the-art, with the goal of publishing your work.
You will join us for a 3-month internship (preferred start date: May) focused on Data-Centric AI. In this project, you will tackle the "glass ceiling" of NLU performance: inherent ambiguity in annotation guidelines and label taxonomies. You will move beyond traditional noise reduction to investigate why human annotators disagree and how these disagreements corrupt "ground truth," directly influencing how we evaluate and improve state-of-the-art models.
Key Job Responsibilities and Duties:
Survey the Landscape: Conduct a comprehensive literature review to synthesize current approaches to data ambiguity, identifying the strengths and limitations of existing methods in handling label noise and taxonomy gaps.
Innovate & Design: Devise novel techniques and metrics to detect, quantify, and resolve inherent ambiguities within NLP datasets and annotation guidelines.
Experiment & Validate: Design and execute rigorous experiments to evaluate your proposed methods, measuring their impact on model reliability and ground truth accuracy.
Publish Findings: Summarize your conclusions and contribute to writing a research paper with the aim of submitting to a top-tier NLP conference (e.g., ACL, EMNLP).
Requirements:
Active PhD student in Computer Science, Computational Linguistics, Machine Learning, or related field.
Proven experience with NLP projects involving tasks such as: Intent detection/recognition, Named Entity Recognition (NER), Sentiment analysis, or Entity extraction.
Strong expertise in PyTorch and proficiency in Python and common NLP/ML libraries (huggingface, scikit-learn, pandas, numpy).
Excellent analytical and problem-solving skills.
Strong written and verbal communication abilities.
Ability to work independently and drive research forward.
Active PhD student in Computer Science, Computational Linguistics, Machine Learning, or related field.
Proven experience with NLP projects involving tasks such as: Intent detection/recognition, Named Entity Recognition (NER), Sentiment analysis, or Entity extraction.
Strong expertise in PyTorch and proficiency in Python and common NLP/ML libraries (huggingface, scikit-learn, pandas, numpy).
Excellent analytical and problem-solving skills.
Strong written and verbal communication abilities.
Ability to work independently and drive research forward.
This position is open to all candidates.
