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Research Fellow / Engineer (Humanoid Robotics and Embodied AI) - EA8
Singapore Institute of Technology (SIT)
Singapore
Singapore Institute of Technology (SIT)
Singapore
Schemes of Service: Research Division: Engineering Employment Type: Fixed Term As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to develop industry-relevant applied research skillsets while working on translational robotics and AI projects. The primary responsibility of this role is to support a joint SIT–DSO research project focused on evaluating and developing humanoid robot capabilities for door opening and doorway traversal in human-centric environments. The Research Engineer will contribute to humanoid robot system integration, teleoperation-based data collection, simulation-based synthetic data generation using NVIDIA Isaac Sim, and learning-based policy development for manipulation and locomotion tasks. The role will involve both experimental robotics work and AI model development for sim-to-real humanoid manipulation research. Key Responsibilities Participate in and manage the research project together with the Principal Investigator (PI), Co-PI, and research team members to ensure project deliverables are achieved. Undertake the following responsibilities in the project: i. Humanoid Robot System Integration Configure and integrate humanoid robot hardware and software systems for door opening and doorway traversal tasks. Support calibration, perception, locomotion, manipulation, and control pipeline integration. ii. Experimental Testbed Development Design and set up representative door interaction experimental environments. Conduct baseline testing and benchmarking for humanoid manipulation and traversal tasks. iii. Teleoperation and Data Collection Develop and operate teleoperation pipelines for humanoid robot data collection. Collect, process, and manage robot demonstration datasets including perception, robot states, and control data. iv. Simulation and Synthetic Data Generation Develop simulation environments and synthetic data generation workflows using NVIDIA Isaac Sim and Omniverse technologies. Implement domain randomization and scenario variation pipelines for robust sim-to-real learning. v. AI Model Development Support development and evaluation of learning-based control policies using reinforcement learning, imitation learning, and visuomotor learning approaches. Assist in model training, testing, benchmarking, and deployment on real robotic platforms. vi. Research and Technical Reporting Conduct literature reviews and experimental studies related to humanoid robotics and sim-to-real learning. Prepare technical reports, publications, and presentation materials for project reviews and dissemination. Carry out Risk Assessment and ensure compliance with Workplace Safety and Health regulations. Coordinate procurement and liaison with vendors/suppliers. Work independently and within a multidisciplinary team to ensure proper operation and maintenance of robotics equipment and experimental infrastructure. Assist in co-supervision of Final Year Project (FYP) or capstone students together with the project PI. To communicate and liaise with internal and external stakeholders to ensure project deliverables are met. Any other ad-hoc duties assigned by Supervisors. Key Requirements Bachelor’s, Master’s, or PhD degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related fields. Experience in robotics software development using ROS/ROS2. Experience with robotic simulation platforms such as NVIDIA Isaac Sim, Isaac Lab, Gazebo, or MuJoCo. Familiarity with humanoid robots, robotic manipulators, or locomotion systems. Knowledge of machine learning, reinforcement learning, imitation learning, or computer vision techniques for robotics applications. Strong analytical and problem-solving skills. Good written and verbal communication skills. Ability to work independently and collaboratively in multidisciplinary teams. The following will be advantageous: Experience with teleoperation systems and data collection pipelines. Experience with NVIDIA Omniverse or sim-to-real workflows. Experience with reinforcement learning frameworks or visuomotor policy training. Experience working with dexterous hands or humanoid manipulation platforms. Key Competencies Strong interest in robotics and embodied AI research. Able to build and maintain strong working relationships with internal and external stakeholders. Self-directed learner with strong initiative and ownership of work. Strong analytical and critical thinking skills. Proficient in technical writing and presentation. Able to work effectively in experimental and rapidly evolving research environments.
Salary
Competitive
Posted
8 Jun 2026
Post-Doctoral Associate in the Division of Science (Mathematics) - Dr. Mostafa Sabri
New York University Abu Dhabi Corporation
United Arab Emirates, Abu Dhabi
New York University Abu Dhabi Corporation
United Arab Emirates, Abu Dhabi
Description The Mathematics Program in the Science Division, New York University Abu Dhabi, seeks to recruit a post-doctoral associate to work on one or more of the following topics: Mathematical Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be considered. This position is offered through the research funds of Mostafa Sabri. The Mathematics Program at NYUAD is quickly expanding, the candidate will find many international experts and postdocs with whom to interact. Weekly seminars are in place across the various research areas represented at NYUAD. The successful applicant will also receive a mobility credit to participate in conferences. Applicants must have a PhD in Mathematics, with a strong background in one of the advertised topics, as well as an excellent academic record. Candidates with PhDs in Physics or Computer Science may also be considered if they willing to collaborate with mathematicians on these topics. For consideration, applicants need to submit a cover letter, a curriculum vitae with a full publication list, a research statement, a transcript, and at least two letters of reference, all in PDF format. Shortlisted candidates will be interviewed twice. In the first interview, the candidate will give a talk summarizing earlier research. The second interview will be to discuss a research project in collaboration with Mostafa Sabri around the aforementioned topics. Candidates are advised to reflect upon such collaborations and include them in the research statement before applying. The duration of the postdoc is for 2 years, with a probation period of 6 months. The starting date is flexible but most likely to be in Fall 2025. If you have any questions, please email Mostafa Sabri at mostafa.sabri@nyu.edu. The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled. About NYU Abu Dhabi: NYU Abu Dhabi is a degree-granting research university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in their pursuit of academic and scholarly activity. This global university represents a transformative shift in higher education, one in which the intellectual and creative endeavors of academia are shaped and examined through an international and multicultural perspective. As a major intellectual hub at the crossroads of the Arab world, NYUAD serves as a center for scholarly thought, advanced research, knowledge creation, and sharing, through its academic, research, and creative activities. EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender Identity Employer UAE Nationals are encouraged to apply.
Salary
Competitive
Posted
8 Jun 2026
Student Support Coordinator
University of Surrey
United Kingdom, Guildford
University of Surrey
United Kingdom, Guildford
The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research. We are ambitious and have a bold vision of what we want to achieve - shaping ourselves into one of the best universities in the world, which we are achieving through the talents and endeavour of every employee. Our culture empowers people to achieve this aim and to collectively, and individually, make a real difference. The role The Student Support Coordinators deliver high quality student support via the University’s one stop shop (the MySurrey Hive) ensuring students receive an exceptional customer focused information service and a memorable and high-level student experience. The Student Support Coordinators are assigned to students whose queries to the MySurrey Hive are complex / multidisciplinary or because they need a higher level of support due to challenges they are facing. It is the role of the Student Support Coordinator to liaise with all of the individual teams and support services needed to resolve the students issues and provide a single point of contact for the student while this is happening. Student Support Coordinators will operate in an efficient and highly customer-focused manner which will support the retention and success of all students, regardless of their background. Student Support Coordinators will also work with students identified via Learning Analytics or referred through Personal Tutors and Senior Personal Tutors. They will work closely with students to ensure that they are supported at Surrey, that they belong to the Surrey community and that they are empowered to achieve their potential. About you We are looking for a well organised, enthusiastic individual with a genuine interest in supporting students. You work well in a team and will be familiar with working autonomously and as part of a wider team; interacting with other support services. You’ll be able to offer guidance to students and staff. Training will be in place to support you, your team and help you develop in the role. If you are enthusiastic, keen to join the University, are motivated to provide an excellent experience to our students, we would be delighted to hear from you. Please note current students are not eligible to apply for this role. How to apply Please apply on the University website with your CV and cover letter focusing on the competencies outlined in the key elements of the role. For informal queries, please email Bryony Turner - Student Support Team Manager: b.c.turner@surrey.ac.uk Interviews will be held on Wednesday 1st July. Further details Job Description
Salary
£32,080 to £36,636 per annum
Posted
8 Jun 2026
Junior Research Scientist in the Division of Science (Computer Science) – Dr. Riyadh Baghdadi
New York University Abu Dhabi Corporation
United Arab Emirates, Abu Dhabi
New York University Abu Dhabi Corporation
United Arab Emirates, Abu Dhabi
Description The Modern Compilers Lab in the Computer Science program at New York University Abu Dhabi, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon are building new specialized programming frameworks. This is because these companies need to allow their users to write simple, high-level code and run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures without changing the code. Our research team at NYUAD (New York University Abu Dhabi) is developing a new programming framework called Tiramisu [1]. Unlike existing frameworks, Tiramisu can perform advanced code optimizations that are hard to apply otherwise. Because of this, Tiramisu can generate fast code that outperforms highly optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations in parallel), enhancing data locality by fusion, and blocking (i.e. accessing arrays in a way that improves temporal and spatial data locality). A large number of optimizations exist and choosing which optimization should be used and which should not is important for performance. In some situations, some optimizations are harmful to performance while they are beneficial in other situations. Currently, there is no way to help users choose which optimizations should be used. Expert programmers usually spend a lot of time trying different optimizations manually to find the best set of optimizations. The goal of this project is to add support for automatic code optimization in Tiramisu. In particular, we want to use machine learning/deep learning to achieve this. Currently, a basic automatic optimization module that relies on machine learning has been developed and we want to take that module to the next level. The final product of this project would be a compiler pass that allows Tiramisu to automatically choose which optimization should be used for a given unoptimized program. We want to produce a high-quality technique that can be used by the users of Tiramisu and especially by our partner companies and research labs. Candidates must hold a bachelor’s degree or equivalent in Computer Science, though a master’s degree is preferred. The ideal candidate will have Internship or experience in the areas of compilers and artificial intelligence. For consideration, applicants need to submit a cover letter, curriculum vitae, transcript, statement of research interests and two letters of reference, all in PDF format. If you have any questions, please email Prof. Riyadh Baghdadi at baghdadi@nyu.edu or mrasras@nyu.edu. The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled. About NYU Abu Dhabi https://nyuad.nyu.edu/en/ NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity’s shared challenges. NYU Abu Dhabi’s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents. NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching. UAE Nationals are encouraged to apply. References [1] http://tiramisu-compiler.org/
Salary
Competitive
Posted
8 Jun 2026
Academic Staff in Cybersecurity
Singapore Institute of Technology (SIT)
Singapore
Singapore Institute of Technology (SIT)
Singapore
Schemes of Service: Faculty Division: Infocomm Technology Employment Type: Permanent, Fixed Term Singapore Institute of Technology (SIT) invites applications for Academic Staff positions in Cybersecurity. We are building a modern cybersecurity capability that brings together applied learning, competency-based education, translational research, and close partnership with industry. We welcome outstanding candidates across the breadth of cybersecurity, and we are especially interested in colleagues who can help SIT build stronger capability in Threat Operations. Appointment may be made at a rank aligned with experience and profile. Academic Staff positions in SIT comprises of both Faculty and Professional Officers. They play distinctive yet complementary roles in advancing SIT’s mission in education and applied research. Faculty provide academic leadership in the design, delivery, and continual enhancement of programmes, ensuring academic rigour and industry relevance, while Professional Officers, as technical specialists, embed current and emerging industry practices and support practice-oriented delivery. Together, they strengthen SIT’s applied learning environment through hands-on, real-world approaches that enhance students’ industry readiness. In applied research, faculty lead translational research and innovation in collaboration with industry, bridging knowledge creation with practical application, while Professional Officers contribute deep technical expertise and industry experience to translate concepts into implementation, prototyping and deployment, thereby ensuring impactful and industry-relevant outcomes. Why join SIT SIT is Singapore’s first University of Applied Learning and the University for Industry. Our students learn in authentic environments, work on real problems with external partners, and undertake substantial workplace learning through the Integrated Work Study Programme. Our approach to education is explicitly competency-based, with a focus on demonstrated capability, workplace relevance, and flexible pathways for learners. At SIT, we welcome both academic candidates, and practitioner-academics with substantial industry, government, or operational cybersecurity experience. Candidates should be able to translate their expertise into rigorous teaching, authentic learning experiences, applied scholarship, translational work, and industry relevant outcomes and impact. Areas of interest in cybersecurity We welcome applicants with expertise in one or more areas across the cybersecurity spectrum, and are especially interested in candidates whose work can strengthen the university’s capability in Threat Operations. Relevant areas include threat detection and analysis, threat hunting, technical investigations, incident response, adversary tradecraft, operational threat intelligence, security operations, and detection engineering. We also welcome applicants working in areas that strengthen operational cyber defence, such as purple teaming, red teaming, AI for security, security automation, adversary emulation, and cyber range or validation environments. Applications from outstanding candidates across the wider cybersecurity spectrum remain strongly welcome. Key Responsibilities You will contribute to SIT’s mission through a combination of teaching, curriculum development, applied scholarship, and external engagement in the area of cybersecurity. Depending on rank and profile, responsibilities may include teaching undergraduate, postgraduate, and continuing education learners designing modules, labs, case-based learning, and authentic assessments supervising capstone projects, industry-linked projects, and graduate students where appropriate contributing to programme development across pre-employment and continuing education offerings building applied research, translational work, or practice-based scholarship with external relevance developing partnerships with industry, government, and professional communities contributing to interdisciplinary initiatives across computing, engineering, AI, and other applied domains Teaching and educational contributions At SIT, strong teaching means building learning experiences that are hands-on, rigorous, and close to practice. That may include secure system design projects, digital forensics investigations, threat-hunting exercises, red-blue or purple-team style activities, malware analysis labs, incident response simulations, or projects shaped by real operational and sectoral constraints. Our educational model values authenticity, workplace relevance, and the ability to assess whether learners can perform, not only whether they can recall. You should be able to contribute to curriculum design, develop modern teaching materials, mentor students well, and work with colleagues to improve programmes over time. Experience with applied learning, competency-based education, workplace learning, or industry-based training will be valuable. Research / scholarly / translational contributions SIT values scholarship that moves beyond publication alone. We are interested in research and scholarly work that can be tested, translated, adopted, or used to solve real problems. This may take different forms: applied research with industry or government; translational work that leads to methods, tools, datasets, or deployable capabilities; practice-based scholarship grounded in operational experience; sector-facing evaluations; or interdisciplinary work that brings cybersecurity into real systems and real environments. The strongest candidates will show a clear line of sight between their expertise and tangible external value. Candidate profile / qualifications We welcome applications from candidates with strong academic, applied, or practice-oriented profiles. You should have Doctorate or a Master’s degree (with substantial and credible industry achievement) in cybersecurity, computer science, computer engineering, information security, or a closely related field expertise in one or more cybersecurity domains relevant to this search demonstrated teaching excellence, or relevant experience in industry-based education and training demonstrated evidence in translating your expertise into authentic learning experiences and useful external outcomes and impact a strong interest in student learning and engagement, and keen to adopt flipped classroom methods, team-based learning, and authentic assessments for learning strong communication skills and a collaborative mindset interest in working across disciplines and with external partners The following will strengthen an application experience in industry, government, or operational cybersecurity environments professional certifications or recognised practice credentials experience with applied or competency-based education a track record in translational research, practice-led scholarship, or industry-linked innovation for candidates at the levels of Associate Professor / Professor, the ability to lead programmes, mentor colleagues, and help shape institutional capability Application Submission Applications will be accepted until the position is filled. All applications must be submitted electronically through the SIT careers website using the Apply Now button. As part of your application, please submit the following materials cover letter curriculum vitae research, scholarship, or applied practice statement teaching statement Questions about this opportunity may be directed to the Cybersecurity Search Committee Chair at SIT_cybersecurity_academic@singaporetech.edu.sg. Only shortlisted candidates will be contacted.
Salary
Competitive
Posted
8 Jun 2026
