De La Salle Medical and Health Sciences Institute (DLSMHSI)

Job Purpose The Professional Officers Division (POD) houses two Innovation Centres – Rapid Product Innovation and Development (RaPID) Centre and SIT-Poly Innovation Centre of Excellence (SPICE) Centre. The RaPID Centre aims to guide businesses in their innovation and value creation activities through rapid product development and sample production while the SPICE Centre aims to support local Small and Medium Enterprises (SMEs) in their technology-driven transformation, innovation and talent development initiatives. These Innovation Centres house a dedicated pool of Professional Officers who come with specialised and deep technical skills acquired through extensive industry experience. Professional Officers work with industry partners to co-create commercially viable solutions. They deliver on projects that help industries and businesses to move up the innovation value chain. While working on these projects, Professional Officers will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands. The success of these initiatives will bring about deeper collaboration with key industry stakeholders that will translate the industry engagement into more innovation projects with SIT. Key Responsibilities Lead or co-lead innovation projects with industry. Involve in customer engagements including gathering of systems requirements and writing project scope. Involve in the full development life cycle, i.e., design, development, and testing Generate technical proposals, design documents, test documents. Manage laboratories and equipment to support academic programmes and applied research. Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations. Job Requirements A degree in Computer Science or related Engineering discipline. Possessing a master’s degree, PhD degree and relevant certifications will be an added advantage. Experienced in developing machine learning and generative AI solutions for deployment into production. Strong proficiency in Python and AI frameworks (TensorFlow, PyTorch, Keras) Strong programming skills in Python/Java/Javascript. Knowledge in LLM, RAG, LangChain would be advantageous. Knowledge of cloud computing and AI deployment (AWS, Google Cloud, Microsoft Azure) would be advantageous. Excellent problem-solving, analytical, and creative thinking skills. Work independently, as well as within a team, to ensure that the project can meet the milestones adhering to the stipulated timeline. At least 2 years working experience in AI/ML software development.

Description Location Abu Dhabi, United Arab Emirates Description The Division of Engineering at New York University Abu Dhabi, seeks to recruit a motivated Research engineer to work under the supervision of Dr. Marwa Chafii on Channel Modeling for integrated sensing and communication (ISAC). Responsibilities: Lead the design, setup, and execution of ISAC channel measurement campaigns across multiple environments, hardware platforms, and frequency bands Develop, validate, and document ISAC channel modeling methodologies tailored to the lab’s hardware/software testbed. Integrate SDRs (e.g., USRPs, RFSoC) and RF front-ends (FR2, FR3, V-band) into end-to-end ISAC demonstrators. Implement and optimize advanced signal processing algorithms for joint communication and sensing. Analyze experimental datasets, extract statistical models, and compare findings across environments, hardware, and frequency bands. Collaborate with PhD students, postdocs, and faculty on joint projects, ensuring experimental results support theoretical work. Co-author scientific publications in IEEE journals and conferences, and contribute to open datasets/methodologies for the research community. Requirements: Education: Ph.D. (preferred) or M.Sc. in Electrical Engineering, Telecommunications Engineering, or a closely related field. SDR Expertise: Strong hands-on experience with SDRs (USRP, RFSoC, or equivalent). FPGA programming experience is a plus. Programming Skills: Strong experience with MATLAB and/or Python; experience with C++ for high-performance signal processing is a plus. Experimentation: Proven experience developing wireless prototypes, demonstrators, or proof-of-concept systems. Signal Processing: Solid knowledge of channel estimation, channel sounding, and multipath modeling (channel impulse response, frequency response, MIMO models, AoA, AoD, delay, Doppler, etc). RF Systems: Familiarity with RF front-ends, antennas, calibration, synchronization, and over-the-air testing. Teamwork: Ability to collaborate in an interdisciplinary environment, working with researchers and engineers at different seniority levels. Communication: Strong written and oral communication skills for preparing technical reports, presentations, and publications. Independence: Proven ability to work independently, from problem formulation, experimental design, and system integration to data analysis and reporting. The candidate will work in a multidisciplinary environment consisting of PhD-level scientists, graduate students and undergraduate students. Applications will be accepted on a rolling basis and candidates will be considered until the position is filled. For consideration, applicants need to submit a cover letter, curriculum vitae with a full publication list,transcript and at least two letters of reference, all in PDF format. If you have any questions, please email Dr. Marwa Chafii at marwa.chafii@nyu.edu. The terms of employment are very competitive and the position provides a salary higher than internationally competitive rates for research associate positions, in addition to substantial benefits (generous housing, transportation and travel allowances, educational subsidies for children), together with full health insurance and retirement contributions. The UAE does not levy income tax. Qualifications This position is not located in the United States. You must be willing to relocate to Abu Dhabi, United Arab Emirates. About NYUAD 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.

THE CENTER FOR MATERIALS INNOVATION AND TECHNOLOGY (CMIT) Materials science underpins nearly every modern technology from clean energy and AI to electronics, biomedicine, defense, and space exploration. The Center for Materials Innovation and Technology (CMIT) aims to become a leading hub for research and international collaboration in advanced materials, driving Vietnam’s strategic technological advancement. CMIT fosters breakthrough innovation in materials for electronics, energy, biomedicine, and sustainability, while nurturing young scientists and future leaders who create knowledge and value for a sustainable future. By 2030, CMIT aspires to be recognized among the world’s leading centers for materials innovation, advancing sustainable technologies, promoting global collaboration, and training a new generation of scientific leaders who transform knowledge into societal and national impact. Research areas: Rare-Earth Materials and Recycling Technologies Sustainable Energy Materials for Green Technologies  Quantum Materials for Next-Generation Technologies AI-Integrated Smart Sensors for Environmental and Healthcare Monitoring  We welcome applications from those with expertise in or across these disciplines: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative AI, or active learning for materials applications. Integration of theory and experiment: Using computation and ML to interpret or guide experimental work. High-performance computing (HPC) and data management for large-scale materials datasets. KEY SELECTION CRITERIA Join us if you have:  Doctorate degree from a globally recognized institution, with expertise in materials science Strong vision for impactful, forward-thinking research and innovation. Proven record of high-impact research and top-tier publications. Passion for education and advancing science through innovative projects. Adaptable and driven to address global and local challenges, especially those relevant to Vietnam. Alignment with VinUni’s core values: Empathy, Exceptional Capability, Creativity, Entrepreneurial Spirit, and Leadership Mindset. PROJECT DESCRIPTION The postdoctoral researcher will contribute to the project “Rare Earth Element Valorisation and Extraction in Vietnam: An Integrated Sustainability Approach” which addresses Vietnam’s strategic need for environmentally responsible and low-carbon pathways for rare earth element (REE) recovery and processing. The project integrates computational modelling, experimental research, fieldwork and appropriate sustainability tools (eg life cycle assessment) to evaluate and develop sustainable REE extraction routes. The postdoc will work on the molecular-level understanding and design of functionalized adsorbents for selective REE recovery from dilute or complex matrices. In addition, the postdoc is expected to conduct experimental and field-based investigations of biomass-assisted and nature-based extraction approaches in Vietnam. ROLES AND RESPONSIBILITIES The postdoctoral researcher will be expected to: Apply computational models (or collaborate with computational experts) for REE–adsorbent interactions. Perform or co-develop environmental impact analyses for REE processing routes. Design and conduct laboratory experiments and selected fieldwork related to biomass-based REE extraction in Vietnam. Analyze and integrate experimental, modeling and environmental-based data to develop sustainability insights. Co-supervise students and contribute to the overall research culture of the group. Present research findings at conferences, workshops and meetings. QUALIFICATIONS PhD in Materials Science, Engineering, Environmental Science, Applied Chemistry or related discipline. Strong record of publications in Journal Citation Indexed (JCR) journals. Qualification or experience in any of the following disciplines: Life Cycle Assessment, Density Functional Theory or Materials Experimentation & Characterization. WHAT WE OFFER A competitive and negotiable salary, commensurate with experience and expertise. The opportunity to work in a dynamic research environment at a leading university in Vietnam. Engagement in cutting-edge sustainability-focused research projects. Collaboration with renowned scientists and industry leaders at the national and international levels. Professional development opportunities including training programmes and participation in international conferences.