HKSTP announces the launch of the Student Internship Programme (SIP) 2026, which has been open for applications since mid-May 2026.-SIP 2026 is designed to equip students with essential skillsets, industry exposure, and professional networks, supporting their transition into the innovation and technology (I&amp;T) sector upon graduation. The programme also enables companies to engage early with emerging talent and contribute to workforce development.-Eligible HKSTP partner companies can receive funding support to employ qualified student interns, providing students with meaningful, hands-on experience in real-world business environments.-*Please note that funding support is allocated on a&nbsp;first-come, first-served basis.-For further details, please feel free to contact TecONE at 2629 2383 or sip@hkstp.org.

HKSTP Student Internship Programme 2026

Blooming with AI: HKSTP Summer Talent Fest 2026

HKSTP Global Internship 2026

HYAB Youth Start-up Internship Programme (YSIP)

“AI for All” Inclusive Programme - Talent Foundry

Why join us?<ul><li>Applied research on a genuinely unsolved problem, measured against published baselines rather than demos.</li><li>Build systems that explain themselves. Every decision has to carry its evidence and the rule behind it.</li><li>Learn from an ex-Google applied machine learning engineer and from practising clinicians.</li><li>Your results change how insurers handle real claims.</li></ul>What you'll work on<ul><li>Research how large language models can read a patient record and assign standard medical classification codes by applying the official coding rules, rather than pattern-matching from training data.</li><li>Build retrieval over versioned rulebooks so the system reasons from current guideline text, and measure whether that grounding changes the answer.</li><li>Design evidence-linked outputs, where every code carries the source sentence and the rule that justifies it, and a deterministic checker rejects anything unsupported.</li><li>Build benchmarks and locked holdout sets, and measure accuracy against published machine learning results and human specialist baselines.</li><li>Design escalation logic that flags cases where the evidence or the rule is unclear, instead of guessing.</li><li>Run error analysis with clinical reviewers, and write up methods and results so another engineer can reproduce them.</li></ul>Requirements<ul><li>Bachelor's degree in a science, technology, engineering or mathematics discipline.</li><li>Solid programming ability in Python or TypeScript.</li><li>Working knowledge of machine learning or natural language processing fundamentals, from coursework, research or personal projects.</li><li>Comfort with experiments. You can form a hypothesis, design a measurement, and read the result honestly.</li><li>Patience with detail. Much of this work is careful reading of structured rules and taxonomies.</li><li>Legally permitted to work in Hong Kong.</li></ul>Nice to have<ul><li>Projects or coursework in natural language processing, information retrieval or retrieval-augmented generation.</li><li>Experience evaluating LLM systems, including building test sets and scoring rubrics.</li><li>Exposure to healthcare, clinical or insurance data, or to any formal classification system.</li><li>Reading knowledge of Chinese or another second language.</li></ul>What makes us different<ul><li>A real research question with real data, at a company small enough that your result ships.</li><li>Direct mentoring from the technical founders on experiment design and method, plus clinical review of your outputs.</li><li>Based at Hong Kong Science Park, inside the wider deep-tech community.</li></ul>LocationOn-site at Hong Kong Science Park, Pak Shek Kok, New Territories.Interested?Send your CV and a short note about a technical problem you have investigated to hiring@heynovo.ai

LLM Research Engineer

Responsibilities<ul><li>Research better robot open-loop and closed-loop control system.</li><li>Research ROS relative algorithms and solutions based on multi sensors, such as, Lidar, IMU etc.</li><li>Research OpenCV algorithms and solutions based on single camera and 3D camera sensors.</li><li>Research Generative AI algorithms and solutions based on our robots.</li><li>Research machine learning algorithms and solutions based on our robots.</li></ul> Requirements<ul><li>Degree in Computer Science/ Automation / Electronic / Mechatronic Engineering or related subject</li><li>Experienced in robot kinematics, robot control, robot simulation and Generative AI. Experienced in C/C++/Python, and ROS.</li></ul>

Robotics Engineer

Responsibilities<ul><li>Develop, optimise, and deploy algorithms involving large language models, computer vision, machine learning, and multimodal AI.</li><li>Translate business requirements into data processing, model training, evaluation, inference optimisation, and continuous iteration.</li><li>Explore technical solutions involving RAG, AI agents, model fine-tuning, knowledge bases, and edge-cloud collaboration.</li><li>Work closely with product, software, and hardware teams to transform AI capabilities into stable, scalable product features.</li><li>Track industry and academic advances, and assess technical direction and practical value in the context of business needs.</li></ul>Requirements<ul><li>A master's degree or above from a university ranked among the world's top 100.</li><li>English is the working language; Mandarin Chinese proficiency is required for daily communication and collaboration.</li><li>Proficiency in Python and familiarity with PyTorch, TensorFlow, or other mainstream deep-learning frameworks.</li><li>Solid foundations in machine learning and deep learning, together with relevant project experience in LLMs, NLP, computer vision, speech, multimodal AI, or reinforcement learning.</li><li>Strong engineering implementation, problem-solving, and cross-functional collaboration skills.</li><li>For candidates with exceptional technical achievements, engineering capability, or industry experience, the academic criterion may be flexibly extended to candidates whose relevant subject is ranked among the world's top 100.</li></ul>Preferred qualifications<ul><li>Experience with model deployment, inference acceleration, MLOps, edge AI, or embedded AI.</li><li>Open-source contributions, research publications, competition awards, or experience taking an AI product from zero to one.</li><li>Familiarity with cloud AI services, vector databases, containerisation, and API-based architectures.</li></ul>Compensation and support<ul><li>PhD: first-year base compensation of HKD 700 k to 1,000 k, inclusive of local allowances. There is no upper limit for exceptional candidates.</li><li>Master's degree: first-year base compensation of HKD 400 k to 700 k, inclusive of local allowances.</li><li>A year-end bonus of no less than two additional months' salary.</li><li>An indexed compensation plan, with annual increases no lower than local CPI, together with MPF contributions and employee insurance.</li><li>Access to Hong Kong's major innovation and technology ecosystem, as well as innovation resources and policy support across the Greater Bay Area.</li><li>Assistance with Hong Kong work-visa and residence-status applications for eligible candidates and qualifying dependants.</li><li>A high-quality office environment in Kowloon Tong. For Hong Kong-based roles, single-room talent accommodation with Victoria Harbour views in West Kowloon is subsidised at 50% of market rent.</li></ul>

AI Algorithm Engineer

The Principal Scientist will oversee the process integration from LED wafers and backplanes to final micro-LED display panel/module products.Job responsibilities include<ul><li>Report to the CEO about the micro-LED project update</li><li>Plan and manage all R&amp;D projects</li><li>Upkeep technological development road-map and future trends based on the latest market demands</li><li>Lead a team of researchers to develop, evaluate &amp; characterize micro-LED display product processes and corresponding process tolerances</li><li>Conduct quantitative and qualitative research to improve existing micro-LED process efficiency and yield</li><li>Provide technical support to answer internal/external inquiries</li><li>Review the team’s experimental work, data, and reports to ensure accuracy and compliance</li><li>Provide technical guidance, training, and support to team members Qualifications: </li><li>Ph.D. in Electronic/Electrical Engineering, Mechanical Engineering, or equivalent, with a background in LED/micro-LED active/passive matrix displays (&gt;5 years R and D experience).</li><li>Sound knowledge &amp; working experiences in micro-LED devices/panel processes, including ICP etching, CVD/PVD, sputtering, e-beam evaporation, flip-chip bonding, and packaging processes.</li><li>Knowledge in quantum dot color conversion, and mass transfer technology.</li><li>Familiar with semiconductor mask design software (such as L-Edit).</li><li>Knowledge of micro-lens, projector systems, and colorimetry is a plus.</li><li>Proactive; Good interpersonal and presentation skills in a cross-functional team; high sense of responsibility and good coordination skills</li><li>Excellent command of written and spoken English as well as Mandarin. Able to read &amp; summarize patent/journal publications </li></ul>

Principal Scientist

Position Overview: The Frontend Research Engineer is responsible for designing, developing, and optimizing User Interfaces (UI) and User Experiences (UX) across interactive smart hardware devices, mobile terminals, and cloud-based management platforms. This role focuses on delivering high-performance, low-latency, and privacy-compliant frontend web interfaces that handle complex dynamic data visualization and responsive layout adaptation.Key Responsibilities:<ul><li>Interactive Terminal UI Development:</li><ul><li>Develop responsive frontend user interfaces for multi-screen hardware terminals, self-service kiosks, mobile devices, and desktop web applications.</li><li>Implement adaptive layout frameworks ensuring seamless visual presentation and smooth touch/voice interaction across various screen dimensions.</li></ul><li>Cloud Platform &amp; Dashboard Implementation:</li><ul><li>Build scalable, multi-language (Traditional Chinese, Simplified Chinese, English) web management portals and analytics dashboards.</li><li>Develop modular UI components for dynamic charts, real-time alert logs, custom rule configuration panels, and historical data querying.</li></ul><li>Privacy Compliance &amp; Frontend Data Protocols:</li><ul><li>Implement frontend security standards and privacy-compliant data handling mechanisms.</li><li>Engineer automatic local cache releasing protocols upon transaction or session termination to ensure strict data privacy adherence.</li></ul><li>Frontend Performance Optimization:</li><ul><li>Optimize web assets, DOM rendering, and API fetch mechanisms to minimize page loading times and interaction latency.</li><li>Collaborate with backend and hardware engineers to optimize WebSockets and real-time streaming data rendering for smooth dashboard performance.</li></ul></ul>Core Competencies &amp; Skills:<ul><li>Proficient in modern frontend frameworks (e.g., React, Vue.js, or Angular) and Web UI component libraries.</li><li>Expertise in responsive design, CSS/SASS, JavaScript/TypeScript, and asynchronous API data handling.</li><li>Experience in optimizing web rendering performance, memory management, and implementing data privacy protection protocols. Requirements:· - Bachelor’s degree or above in Computer Science or Software Engineering - Minimum 1–2 years of frontend R&amp;D experience· - Proficiency in React / Vue / TypeScript - Experience in cross-platform UI development and adaptive layouts - Familiarity with Web accessibility or privacy-compliant frontend logic Preferred Qualifications:· - Participation in R&amp;D-oriented projects (not purely commercial outsourcing) - Experience in multilingual interface design - International work experience</li></ul>

Frontend Research Engineer

Key Responsibilities<ol><li>Design, build and maintain end‑to‑end AI data pipelines for construction‑site AI projects, including multi‑modal (RGB + IR) dataset acquisition, pre‑processing, alignment, quality control via clustering methods (KMeans, HDBSCAN), data augmentation and annotation standardisation; improve dataset consistency for facade defect detection, on‑site hazard detection and intelligent tower crane modules.</li><li>Develop, train, tune and benchmark deep‑learning models using PyTorch for construction computer‑vision tasks: object detection (YOLO family), keypoint detection and pose estimation for tower‑crane hook stabilisation and site safety monitoring. Measure recall / precision / accuracy and iterate augmentation strategies and model configurations to lift real‑world performance metrics.</li><li>Support data engineering for the AI‑powered Intelligent Tower Crane System: manage on‑site raw data collection, cleaning and validation for hazard detection and hook‑stabilisation modules; analyse system performance and contribute to accuracy and operational efficiency improvements.</li><li>Implement Retrieval‑Augmented Generation (RAG) pipelines for internal research; integrate multi‑retriever modules (BM25, dense retrievers, ColBERT, E5 / GTE‑Qwen‑Instruct), open‑source LLMs, conduct quantitative evaluation using MAP, NDCG, precision and recall metrics. Explore potential LLM / agent‑AI use cases for construction‑site documentation, incident analysis and technical knowledge retrieval.</li><li>Build NLP solutions such as text tokenisation, feature extraction and supervised text classification; process structured / unstructured text data including project reports, site incident records and technical documentation.</li><li>Perform statistical analysis and exploratory data analysis (EDA) using Python and R; conduct quantitative analysis on construction‑site operational data, safety incident datasets and experimental model outputs.</li><li>Construct and optimise ETL workflows; manage SQL and NoSQL (MongoDB) databases, integrate multi‑source datasets to build AI‑ready data infrastructure for construction‑tech research and decision‑making.</li><li>Collaborate cross‑functionally with research and engineering teams, analyse model error cases from real‑world site data, document experimental workflows, model performance and technical findings; support report generation and data visualisation via Power BI / Matplotlib / Seaborn.</li><li>Keep track of state‑of‑the‑art advances in LLM, agentic AI systems, multimodal deep learning and computer vision; prototype new techniques and adapt them for construction robotics, site safety and intelligent tower‑crane research projects.</li></ol>RequirementsEducation<ul><li>Master’s degree in Data Science &amp; Analytics, Statistics, Computer Science, or related quantitative disciplines; Bachelor’s degree in Statistics or relevant STEM field is required.</li><li>Exposure to multimodal learning, computer vision or applied data analytics for engineering domains is an advantage.</li></ul>Technical Competencies<ul><li>Strong programming skills in Python, PyTorch; practical experience with R, SQL, Git.</li><li>Hands‑on project experience building RAG pipelines, NLP text classification, sentiment analysis, computer vision (YOLO‑based detection &amp; keypoint detection), multimodal deep‑learning frameworks.</li><li>Solid experience in data engineering: multi‑modal dataset building, data cleaning, ETL, dataset QC, database handling (MySQL, PostgreSQL, MongoDB).</li><li>Familiar with statistical methods, exploratory data analysis; hands‑on experience evaluating CV / NLP models with metrics including MAP, NDCG, recall, precision, AUC.</li><li>Working knowledge of visualisation tools: Power BI, Pandas, NumPy, Matplotlib, Seaborn.</li></ul>

Research Assistant(Data Science and Analytics)

Main job duties： ①Lead R&amp;D of AI-driven end-to-end unmanned logistics systems in Hong Kong (warehousing / sorting / transfer / communications integration) ②Optimise AI dynamic scheduling algorithms for HK cross-border logistics ③Integrate local supply chain systems, customise intelligent WMS &amp; unmanned operation control modules with on-site commissioning ④Build digital twin simulation platform for order-peak scenarios ⑤Lead IP filings and industry-academia-research collaboration Minimum entry requirement： - Bachelor's degree in [STEM-related subjects] or related subjects with at least 3 years of working experience; - Master's degree in [STEM-related subjects] or related subjects with at least 1 year of working experience; - Doctoral degree holder in [STEM-related subjects] or related subjects (working experience is not compulsory); - HCAI AI certification is preferred.

Title of job position：Senior R&D Engineer of AI Supply Chain Logistics Unmanned Systems

🔹 学历要求：<ul><li>博士学历；</li><li>有机合成、有机化学、应用化学、精细化工、药物化学、化学工程与工艺等化学相关专业；</li><li>具备扎实的有机化学基础理论与反应机理知识，有独立开展课题研究的经历。</li></ul>🔹 工作经验：<ul><li>博士学历，具备独立开展有机合成研发项目的能力，有完整的合成路线设计、小试开发到工艺优化落地经验；</li><li>优秀应届博士毕业生可投递（公司针对博士可争取博士后入站及出站补贴名额）；</li><li>有博士后经历或精细化工、有机合成相关研发经验者优先。</li></ul>🔹 职位详情（岗位职责）：<ol><li>负责高端有机小分子功能助剂、精细化工添加剂的合成路线设计、小试开发、工艺优化及提纯精制等全流程研发工作，保障实验规范、数据可靠。</li><li>配合团队分子选型成果，完成目标小分子定制合成与结构改性，输出稳定、可落地、可放大的合成工艺方案。</li><li>结合产品应用及量产反馈，迭代优化合成工艺，解决副反应、纯度、收率等技术问题，保障产品批次稳定，优化生产成本。</li><li>整理复盘实验数据，完成工艺总结与技术文档编撰归档，沉淀研发技术经验。</li></ol>🔹 任职要求：<ol><li>专业能力：精通各类常规及高端有机合成反应，能独立完成有机小分子、功能助剂的合成路线设计、小试开发及工艺迭代优化。</li><li>实验技能：熟练掌握萃取、重结晶、精馏、柱层析等提纯精制工艺；熟练操作 HPLC、NMR、GC-MS 等检测设备，可独立完成产物检测、数据分析与结构验证。</li><li>问题解决：具备严谨的科研思维，可精准解决合成过程中纯度、收率、工艺稳定性等核心技术问题，擅长数据复盘与工艺优化。</li><li>文档规范：具备规范的技术文档撰写能力，能高效完成实验记录、工艺报告等研发资料的整理归档。</li><li>加分项：<ul><li>具有博士后研究经历，或发表过高水平 SCI 论文（一作）者优先；</li><li>有精细化工助剂、有机催化剂、功能性精细小分子合成研发经验者优先；</li><li>具备定制化小分子合成、结构改性、工艺放大优化实操经验者优先；</li><li>具备量产或工艺放大经验的博士，可作为研发骨干重点培养。</li></ul></li><li>综合素质：良好的团队协作与沟通能力，工作严谨负责、善于学习创新，可适配港深双基地研发节奏，抗压能力良好，恪守科研诚信与安全意识。</li></ol>🔹 福利待遇：<ul><li>薪酬：极具竞争力的薪资待遇（面议，博士薪资不设上限，优秀者可放宽预算）；</li><li>保障：五险一金、带薪年假、节日福利、年度体检；</li><li>补贴：双基地办公补贴（深港通勤支持）；</li><li>激励：绩效奖金、定期行业技术交流；</li><li>发展：完善的职业晋升体系；</li><li>博士专属：可协助申请博士后入站，争取出站补贴名额，增加额外收入。</li></ul>🔹 应聘方式：请将个人简历及相关科研、项目佐证材料发送至招聘邮箱：📧 jennie.zhou@dynano.com

有机合成研发工程师

Key Responsibilities:<ul data-spread="false"><li>Develop and execute the company’s technology strategy, R&amp;D roadmap and product development plan.</li><li>Lead the research, development and engineering application of innovative pavement materials, recycled asphalt technologies and low-carbon road solutions.</li><li>Transform research outcomes into scalable, market-ready products and technical services through laboratory testing, field trials and performance validation.</li><li>Build and manage the R&amp;D team </li></ul>Requirements:<ul data-spread="false"><li>PhD degree in Road Engineering, Pavement Materials, Civil Engineering, Materials Science or another related field.</li></ul>

Where Talent Meets Opportunity