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Research Associates / Research Assistants

The National University of Singapore invites applications for research assistant/associates in the Multimodal Neuroimaging in Neuropsychiatric Disorders Laboratory (MNNDL), Center for Sleep and Cognition at the Department of Medicine, Yong Loo Lin School of Medicine.

The MNNDL group at NUS studies the human neural bases of cognitive functions and the associated vulnerability patterns in aging and neuropsychiatric disorders using multimodal neuroimaging and psychophysical techniques. We are interested in the large-scale brain structural and functional networks in healthy developing and aging brain and symptoms-related changes in diseases such as neurodegenerative disorders and psychosis. Statistical, computational, and machine learning methods are developed to analyze and fuse multimodal neuroimaging data. By integrating longitudinal behavior, neuroimaging, and genotype data, our long-term goal is to investigate the interactions among brain network dynamics, behavior, diseases, and genotypes to develop non-invasive biomarkers for early detection, differential diagnosis, progression monitoring, and treatment design.

Key attractions are access to a high-performance computing cluster, two 3T Prisma MR scanner and a MR compatible digital EEG system as well as collaboration opportunities with an excellent network of domestic and international scientists and doctors. Appointments will be made on a two-year contract basis in the first instance, with the possibility of extension. Salary and benefits will depend on qualifications and work experience. Long-term commitment is encouraged with mutual satisfaction.

Purpose:

The Research Associate/Assistant (RA) will be responsible to, and work closely with, the Principal Investigator, lab members, and collaborators to ensure successful completion of research projects and efficient management of database in the lab.

Main Duties and Responsibilities:

The research associate/assistant will support the effort in conducting cutting-edge neuroscience and machine learning research and development. He/she has the opportunity to learn state-of-the-art neuroimaging techniques, data collection and analysis, with healthy participants and patients with neuropsychiatric diseases. He/she will be primarily engaged in all neuroimaging experiments such as subject recruitment, behavioral testing, image data collection, and data analysis, support computing server and storage administration (with support from external vendors), and general lab administration. He/she will also be able to learn how to conduct fMRI scans with EEG recording, interactions with patients, quality control, behavioural assessments, and implications in neuroscience and disease. The research assistant is expected to learn neuroimaging softwares and assist researchers in IRB application, data preprocessing and database management in various research projects. He/she will be exposed to ongoing research work in machine learning and statistical analysis in the context of neuroimaging and cognitive neuroscience. The research assistant/associate will have the opportunity to liaise and work with other clinical collaborators across the institutes/hospitals in Singapore on research projects and contribute to the presentations and publications of research work. He/she will assist with any other duties of a similar nature that are delegated by the principal investigator. He/she is expected to maintain the highest standard of professional conduct and record keeping in accordance with policies and procedures.

Qualifications:

  • Bachelor’s degree or master’s degree with neuroscience/psychology/life science/engineering/computing background with strong interest to learn
  • Excellent written, oral communication skills
  • Prior programming experience in medical image analysis or database management (e.g., MATLAB, shell, python) is a plus but not necessary
  • Seek organized, reliable, self-motivated individual who is able to work effectively with others and multitask efficiently
  • Expected to commit for at least two years

Remuneration will be commensurate with the candidate’s qualifications and experience.

Interested applicants are welcome to email Associate Professor Helen Zhou at helen.zhou@nus.edu.sg with the application letter, curriculum vitae, and contacts of two-three references. Only shortlisted candidates will be notified.

Research Fellows

Candidates must have a passionate enthusiasm for research and a strong background in one of the fields stated below. They should be self-motivated, enjoy working as a team and constantly seek new challenges. They should also possess the ability to take the initiative, work independently and be motivated to work in a highly collaborative and international research environment, and be able to demonstrate creativity, technical independence and excellent communication skills.

Requirements:

  • PhD in one of the following fields: cognitive neuroscience, computational neuroscience, mathematics/statistics/machine learning, neuropsychiatric disorders, neuropsychology, neuroimaging analyses, or related-fields
  • Strong interest in studying cognitive brain networks in aging and neuropsychiatric disorders
  • Strong interest in developing computational/machine learning approach for multimodal neuroimaging data
  • Prior experience in fMRI/EEG/DTI is a plus

Key attractions are access to research-dedicated Siemens 3T MAGNETOM Prisma fit and Prisma MRI scanners, a MR compatible digital EEG system, high-performance computing cluster and storage as well as collaboration opportunities with an excellent network of domestic and international scientists and clinicians. Competitive package will be provided based on experience.

Interested applicants are welcome to email Assoc. Prof. Juan Helen Zhou at helen.zhou@nus.edu.sg with the application letter, curriculum vitae, three references, and contact information.

Graduate Students

Applicants interested in research on machine learning, cognitive neuroscience, computational neuroscience, neuroinformatics, or neuroimaging in neuropsychiatric disorders are welcomed to apply. Key attractions are access to research-dedicated Siemens 3T MAGNETOM Prisma fit and Prisma MRI scanners, a MR compatible digital EEG system, high-performance computing cluster and storage as well as collaboration opportunities with an excellent network of domestic and international scientists and clinicians.

Interested applicants are welcomed to contact Assoc. Prof. Juan Helen Zhou for a discussion at helen.zhou@nus.edu.sg.

Some useful information about PhD programs and scholarships offered in Singapore:

1. Yong Loo Lin School of Medicine, NUS

  • PhD Program at Yong Loo Lin School of Medicine, NUS details can be found here.
  • 2. National University of Singapore (NUS)

  • NUS Graduate School for Integrative Sciences & Engineering (NGS) PhD Program details can be found here.

    3. A*STAR

  • Graduate scholarship details can be found here.
  • Research Interns

    Due to limited lab capacity, our lab can only host a small number of interns each year. Interns join a vibrant research team for a minimum of 3 months (full-time) or 6 months (part-time), supporting ongoing experiments in the course of learning about research in cognitive neuroscience and vulnerability factors of neuropsychiatric disorders.

    To ensure a good fit with the lab, we only consider candidates who demonstrate the following:

  • A keen interest in scientific enquiry
  • Independence
  • A minimum commitment of 3 months (full-time) or 6 months (part-time)
  • There are usually three intakes each year: May - Aug (vacation), Aug - Jan (school term 1), and Jan - July (school term 2). Application interview and review process usually begins 2 months prior to the intake. Schedule is subject to changes depending on the need and resources in the lab.

    If you are keen to do an internship with our lab, please email both Assoc. Prof. Juan Helen Zhou at helen.zhou@nus.edu.sg and cc Dr. Eric Ng at eric.nkk@nus.edu.sg with the application letter, curriculum vitae, transcript, and the possible letter of endorsement/school requirements.