The International Medical University (IMU) is the pioneer and leading private healthcare university in Malaysia. Backed by overseas partner universities and a proven track record in high quality healthcare academic programmes, we are seeking candidates with a desire for accomplishment to join us.


Prof Chu Wan Loy Dean, School of Postgraduate Studies International Medical University No 126, Jalan Jalil Perkasa 19, Bukit Jalil, 57000 Kuala Lumpur E-mail: [email protected]

Career-Research Positions Vacancy




  • "GRA advertisement for MSc and PhD by Research"
    Opening for Graduate Research Assistant (GRA)

    Applications are invited from suitably qualified candidates for the post of Graduate Research Assistant (GRA) at the International Medical University (IMU). The post is especially for candidates who are interested in pursuing an MSc or PhD in Medical & Health Sciences (by Research) degree. The candidature is for a duration of 2 years for MSc and an additional year for PhD. Candidates who intend to work on projects related to translational research, system biology, data analytics, and environmental and population health will be given priority.

    The tuition fees of the successful candidate will be waived while pursuing the postgraduate degree. The candidate will also receive a monthly salary of RM1,800. The job scope of GRA includes assisting in the running of the IMU Research Laboratory, and taking charge of specific equipment and facilities (e.g. HPLC and ICP-MS).

    The applicant should possess a first degree, preferably in health sciences with a minimum cGPA of 2.75. Application should include a cover letter and resume, and be sent to:

    Prof Chu Wan Loy
    Dean, School of Postgraduate Studies
    International Medical University
    No 126, Jalan Jalil Perkasa 19, Bukit Jalil, 57000 Kuala Lumpur
    E-mail: [email protected]

    The closing date for the application is 1 October 2017.

    Only shortlisted candidates will be called for an interview.
  • "Mechanistic basis of tumour evasion from cytotoxic T cells (CTL) surveillance in pancreatic cancers"
    Candidate for Research Assistant.

    Project Description: Pancreatic cancers (PC) is among the deadliest of malignancies with a 5-year survival rate of <10%. PC is unique from an immunological perspective as the tumour exist in an immune privileged environment where the presence of many immune cells, particularly the effector cytotoxic T cells (CTL), in the tumor microenvironment is common, but dysfunctional. Hence, immunotherapeutic approaches to the treatment of PC remain elusive, despite their superior efficacy demonstrated in the treatment of other solid tumours. The goal of this proposal is to investigate the cancer cell-autonomous mechanisms that could lead to resistance to CTL-mediated cytotoxic effects in PC cells. The specific aims are:

    1. To identify immune-checkpoint molecules and tumour intrinsic factors that mediate tumor resistance to CTL-mediated cytotoxic effects in PC.

    2. To validate the functional role of the candidate modulators in an in vitro model.

    3. To validate the expression of the candidate modulators and their correlation with clinical outcomes in primary PC.

    Scholarship/Stipend: Stipend


    Education & Knowledge

    - A bachelor's degree or equivalent with minimum CGPA of 2.75 in Medicine, Pharmacy or Health Sciences related course. Priority will be given to First Class Honor degree holder.
    - The Standard English Proficiency requirements are overall band scores of IELTS 6.0 or TOEFL 550 (PBT) or 79 (IBT), TOEIC 620, Pearson 55 (PTE), Cambridge 45 (CPE) or 52 (CAE) or MUET band 4 or any other equivalent recognised English language qualification.

    - Additional qualification/training in cancer research.


    - Experience in cell biology, biochemistry, molecular biology (quantifying gene and protein) and gene knockdown in human cell culture
    - Familiarity with contemporary approaches molecular target identification and validation
    - Experience in bioinformatics analysis
    - Experience in retrieving data from public domains such as International cancer Genome Consortium (ICGC) and the National Cancer Institute (NCI, USA) Genomic Data Commons Data Portal
    - Experience in identifying, understanding, summarising and critical analysis published research papers


    - Good collaborative and communication skills

    - Range of skills in cell biology, biochemistry, molecular biology (quantifying gene and protein) and gene knockdown in human cell culture
    - Proficient use of PCs (e.g. Microsoft Word, Excel and PowerPoint) and databases
    - Proficient in oral presentation
    - Proficient in written presentation
    - Proficient in statistical analysis


    - Enthusiasm to work in an interdisciplinary environment towards the goal of developing improved cancer therapies.
    - Highly motivated and strong desire for excellence
    - Can prioritize work to meet deadlines
    - Attention to detail and accuracy
    - Ability to work independently and as part of a team
    - Responsibility and accountability
    - Professionalism and avoid from any possible professional misconduct

    Duration: 2 years

    Commencement date of the project: 1 Oct 2017

    To apply, please submit your CV and covering letter to [email protected] by 15 September 2017. In your covering letter, please address with specific examples where you meet the person specification (if not, how would you plan to overcome your shortcoming if you are joining the team) and summarise your research interests and motivation for applying. Please include the names and addresses of two referees. Informal enquiries can be made to [email protected].
  • "Big Data Statistician"
    Centre for Translational Research (CTR), Institute for Research, Development and Innovation (IRDI), International Medical University, Bukit Jalil Campus.

    Responsible to: Prof Mak Joon Wah, Prof Patricia Lim & Dr Ivan K. S. Yap

    Job Purpose & Scope: The CTR has a vacancy for a Lecturer position in Big Data Statistical Modelling, to contribute to its overall research programme, centring on statistical learning applied to large health datasets. We are seeking a scientist with significant, relevant and up to date knowledge in statistics, machine learning and big data science. The mandatory requirement for the Lecturer post is a PhD.


    Key accountabilities

    - Expertise in statistical learning and big data science to support and drive research outputs in IRDI and the CTR.
    - Methodological and applied scientific excellence in support of IRDI and the CTR.

    Responsibilities and tasks

    - Provide expertise in statistics, machine learning and big data science with a range of health problems and datasets under the guidance of centre head and IRDI head.
    - Contribute to the development and management of research capability focused on extracting knowledge from large repositories of research and healthcare data.
    - To contribute to the intellectual development of IRDI and the CTR in the specific area of expertise through world-class research.
    - Work with fellow CTR and IRDI members to develop novel computational/statistical analysis approaches and algorithms.
    - Contribute to the publishing of results of original research in international journals and conferences of high standing.
    - Publish the results of original research as first author in international journals and conferences of high standing.
    - To contribute to the development of funding proposals for both research council and industry partners.
    - Contribute to communications with HeRC, CHI staff & affiliates, key stakeholders, opinion-leaders, policy-makers, and public and patient interest groups, as required.
    - To contribute to, and support, IRDI and the CTR research strategies through the development of new collaborations.
    - To play an active part in developing the academic culture in IRDI and IMU.
    - To keep up to date with knowledge of emerging technologies and new strategic directions that develop in this fast moving environment.

    Person Specification

    Essential Knowledge, Skills and Experience

    - A PhD in Statistics or similar allied fields (such as mathematics or computer science with focused on statistical modelling).
    - Previous relevant experience in academia or industry encompassing a strong health informatics and biostatistics background, preferably with experience in the analysis of complex healthcare problems and datasets.
    - Advanced knowledge of probability theory, statistics and machine learning (also for dynamical/longitudinal modelling).
    - Significant statistical modelling and programming experience.
    - Advanced knowledge of one or more high-level modelling languages such as R and Matlab, SAS, Stata.
    - Capability of handling big data (e.g. usage of R libraries such as ff, bigdata, bigglm, snow).
    - Basic knowledge of relational data bases and SQL.
    - Emerging record of publications in peer-reviewed journals, including some as first author.
    - Ability to explain complex statistical issues to a non-statistical audience.
    - A proven ability to work effectively within a team to achieve timely and valued objectives.
    - Excellent presentation skills.

    Desirable Knowledge, Skills and Experience

    Further knowledge and experience in one or more of the following:

    - Generative modelling and Bayesian learning besides standard classification/regression methods (e.g. latent class modelling, Gaussian processes, Bayesian network learning).
    - Deeper theoretical knowledge of machine learning techniques
    - Knowledge of other data mining/analysis software suites such as Weka, Orange, KEEL.
    - Knowledge of different programming languages (preferably Java or C++), data structures and algorithms.
    - Knowledge of data base theory and data warehousing software (e.g. object-oriented database management system (DBMS), XML Schema definition (XSD), data integration platform such as Kettle/Pentaho).
    - Knowledge of distributed/network computing & big data science (e.g. parallel virtual machine (PVM), message passing interface (MPI), ScaleMP, MapReduce/Hadoop)

    Candidates should email a cover letter, curriculum vitae, and a statement of research interests to Dr. Ivan Yap Kok Seng ([email protected]), the Head of the Centre for Translational Research, IRDI, by 4 September 2017.

    Please also provide the names, addresses, and telephone numbers of at least two references. Shortlisted candidates may be called for an interview.
  • "Nanoformulation of rotigotine intended for direct nose to brain targeting in Parkinson disease"
    Candidate for MSc


    Title: Nanoformulation of rotigotine intended for direct nose to brain targeting in Parkinson disease

    Project Description: Parkinson's disease (PD) is a brain disorder that causes trembling of hands and slowness of movement. It is most common after the age of 60. It is estimated that about 15,000 to 20,000 individuals suffer from PD in Malaysia. Oral levodopa represents the most widely used drug for the treatment of PD. However, chronic treatment with oral levodopa leads to development of severe motor complications and dyskinesias. Therefore, improvement of motor complications remains a significant unmet clinical need in the treatment of PD. Rotigotine is dopamine agonist that has been shown to be effective for the therapy of PD clinically. However, despite the therapeutic potential of rotigotine, its clinical application has been hindered due to low oral bioavailability, extensive first-pass effect and nonspecific targeting. Hence, there is a need for an improved drug delivery system which would increase bioavailability of rotigotine and provide site-specific deposition in the brain. This project aims to investigate direct nose to brain delivery system for rotigotine using polymeric nanoparticles to improve the clinical potential of rotigotine for the treatment of PD. This technology has the potential of improving drug delivery to the brain and thus drug efficacy and reducing the spiraling healthcare costs associated with neurodegenerative diseases including PD.

    Scholarship/Stipend: RM 2000/-

    Entry requirement:
    - Relevant Bachelor Degree in Science (B.Pharm/Pharm chemistry / Biomedical / Molecular Medicine) - Preferably a Malaysian citizen
    - Possess basic MS Office skills
    - Self-motivated and be able to work independently on a lab based project
    - Have good interprofessional skills

    Duration: 2 years

    Commencement date of the project: August

    Interested candidates can contact Dr. Shadab Md, ([email protected]) for further details. Alternatively, you may call directly at 0172071973 and 0327317061 Ext: 1335.


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