We have multiple positions available in various Computational Biology groups.
GROUP OF PAVITRA KRISHNASWAMY (I2R – PRECISION MEDECINE)
A research scientist position is available immediately at the Institute for Infocomm Research (I2R), A*STAR, Singapore. The project focuses on development of machine learning, deep learning and artificial intelligence algorithms for applications in precision medicine.
Specific research themes include:
- Multimodal data analytics on heterogeneous healthcare datasets (genomics, EMR, imaging, lifestyle) to predict treatment response and/or patient outcomes
- Methods to incorporate domain knowledge with machine learning and deep learning approaches for biomedical data analysis
- Interpretable machine learning and deep learning approaches for biomarker identification, knowledge discovery and clinical applications
The position entails working in a multi-disciplinary machine learning and deep learning team in close collaboration with bioinformatics experts, biologists, clinicians, as well as other leading academic and industry partners on impactful projects that have the potential to transform patient-care and deliver improved health outcomes. Appointments will be based in Singapore for 3 years duration.
A research engineer position is available immediately at the Institute for Infocomm Research (I2R), A*STAR, Singapore. The project focuses on development of machine learning, deep learning and artificial intelligence algorithms for applications in precision medicine.
Candidates should have demonstrated interests or experience in one or more of the following:
- Analysis of large scale heterogeneous biomedical datastreams (genomics, EMR, imaging, lifestyle)
- Projects involving biomarker identification, knowledge discovery, predictive analytics for patient outcomes,
and/or clinical application
- R&D for advanced algorithms
Core responsibilities include preprocessing of raw disparate biomedical datasets, development of automated knowledge extraction and feature engineering pipelines, and design of pilot studies/demos. The position entails working in a multi-disciplinary machine learning and deep learning team in close collaboration with bioinformatics experts, biologists, clinicians, as well as other leading academic and industry partners on impactful projects that have the potential to transform patient-care and deliver improved health outcomes. Appointments will be based in Singapore for 2 years duration.
to get details on both positions.
To apply, please email your CV and names of references to: Pavitra Krishnaswamy
Group of Niranjan Nagarajan (Sequence Analysis and Metagenomics)
We study the role of microbial communities in human health and disease using integrative omics approaches and systems models, combining wet and dry-lab expertise. We also frequently develop novel statistical and combinatorial algorithms for the assembly and analysis of high-throughput sequencing data (see Gao et al. 2011, Wilm et al. 2012, Bertrand et al. 2014). Current areas of focus include a) modelling pertubations in the gut microbiome in response to antibiotics and colonization by pathogens b) studying the role of the microbiome in skin diseases, and c) developing algorithms for nanopore sequencing data and RNA structure analysis. Open positions in the lab include:
- Computational PhD
- Postdoctoral Fellow (Skin Microbiome)
- Postdoctoral Fellow (RNA Structural Genomics)
- Bioinformatics Engineer
Lab website: http://csb5.github.io/
GIS website: Niranjan Nagarajan
To apply, please email your CV and names of references to: email@example.com
Group of Shyam Prabhakar (Single-cell Data Analytics and Epigenomics)
The Prabhakar lab at the Genome Institute of Singapore (GIS) is looking for creative and highly motivated PhD students and Postdoctoral Fellows to drive epigenomics and single-cell genomics projects in the areas of cancer and immune aging. We are a well-supported lab (Singapore Agency for Science, Technology and Research; US National Institutes of Health; Singapore National Research Foundation; multiple industry partners) with strong links to clinicians and a track record of combining cutting-edge experimental and computational approaches to infer gene regulatory mechanisms in development and disease (Kumar et al., Nat Biotechnol 2013; del Rosario et al., Nat Methods 2015; Sengupta et al., biorXiv 2016; Cima et al., Sci Transl Med 2016, Sun et al., Cell 2016). In addition to answering basic questions regarding molecular and cellular phenotypes, our current focus is on analyzing cohort-scale epigenomics and single-cell omics data to identify novel cell types, biomarkers and druggable pathways. Open positions in the lab are in epigenomics and single cell analysis of multiple diseases, including lung and colon cancer, tuberculosis, autoimmune diseases and autism:
- Computational Genomics PhD
- Computational Genomics Postdoctoral Fellow
Qualifications: Candidates should have training in a quantitative field, a strong publication record (postdoctoral candidates), strong writing skills, the ability to design new methods and the ability to work closely with clinicians and experimental biologists. Expertise is required in at least some of the following: mathematics, statistics, machine learning, signal processing, next-gen sequence analysis.
GIS website: Shyam Prabhakar
To apply, please email your CV and names of references to: firstname.lastname@example.org
Group of Anders Jacobsen Skanderup (Computational Cancer Genomics)
We develop and apply computational and statistical approaches for cancer research that take advantage of large-scale genomic, molecular, and clinical data. We are particularly interested developing computational approaches to decipher the influence of non-coding elements and transcripts in cancer using rich tumor profiles and massive DNA sequence data (see Weinhold, Jacobsen et al. 2014, Nature Genetics; Jacobsen et al. 2013, Nature Structural & Molecular Biology).
- Postdoctoral Fellow (Computational Cancer Genomics)
- Bioinformatics specialist / Data Analyst (Computational Cancer Genomics)
Lab website: Skanderup lab
Group of Chaolong Wang (Statistical and Population Genetics)
As a computational group, we collaborate closely with biologists and clinicians to study population genetics and various human genetic diseases. We develop and distribute novel statistical and computational methods to address new challenges arise from large-scale human genetics and genomics data when there is no off-the-shelf tool available. More information about our research can be found on our website.
- Postdoctoral Fellow (Statistical and Population Genetics)
- Data Analyst / Research Officer (Statistical and Population Genetics)
Lab website: Wang lab
Group of Jonathan Goeke (Transcriptomics, Cancer Genomics, Machine Learning)
We investigate transcript diversity, alternative splicing, gene regulation, and epigenetics to identify key elements and mechanisms that regulate cellular identity. Our main focus is the large scale cancer data analysis. We are closely collaborating with wet labs to translate computational models to cellular phenotypes.
The Goeke lab is currently searching for PhD students (starting in August 2018) and postdoctoral fellows with a background in bioinformatics, computational biology, computer science or statistics.
The following projects are available for PhD students starting 2018:
- Algorithms for long read transcript quantification
- Statistical modeling of uncertainty using large-scale transcriptomics data
- Machine learning approaches to predict clinical data from genomics data
We are looking for a postdoctoral fellow to work on algorithms for long read transcript quantification. Details about the postdoc position can be found online (https://jglab.org/postdoc-positions/
Lab website: Goeke lab
GIS website: Jonathan GÖKE
Interested candidates can contact Jonathan Göke (email@example.com). Additional information about the Goeke lab: https://www.a-star.edu.sg/gis/our-people/investigator-details.aspx?source=faculty_member&user_id=160
Group of Weiwei Zhai (Evolutionary and cancer genomics)
There are three major directions we are focusing on: a) Cancer genomics, we are taking a population genetic and genomic approach in understanding the evolution of tumors. The major focus of the research is to quantify and understand the origin of intra-tumor heterogeneity. b) Viral population genomics. We are very interested in how virus adapts to the human host. We are developing a computational method based on continuous time Markov Chains to look at viral adaptation systematically. c) The genetics of animal domestication. In the past 10,000 years or so, we have domesticated many plants and animals from the wild. Understanding the evolutionary and genetic basis of animal domestication can provide important basis for animal breeding and disease trait mapping.
- Postdoctoral fellowship, or research officer (RO) position is available in cancer genomics
- Postdoctoral fellowship, position available in Computational Biology with the potential to work on any of the three directions.
Lab website: Zhai lab