Efficiently communicate with other scientists on the project, actively and creatively develop solutions to support the overall project goals.
Combine strong software development skills with a working knowledge of basic chemistry/physics/biology to develop sophisticated informatics solutions that drive efficiencies in data-based insights development.
Build predictive models using machine learning algorithms and frameworks, such as TensorFlow, PyTorch, Scikit-learn etc.
Apply NLP, machine learning, and deep learning in various domains.
Present information and insights using data visualization techniques, such as matplotlib, plotly etc.
Capable of self-directed research within broader goals set by group.
Manage multiple projects at any given time along with tracking project milestones.
Should be able to teach and train his/her team in all the above-mentioned aspects as and when required.
Job Requirements
PhD in Computer Science/ Cheminformatics/ Bioinformatics/ Computational Biology/ Medicinal Chemistry
3+ years of post-degree experience working with large data sets/software development
Experience building applications for public cloud environments (AWS preferred).
Proficiency in programming languages such as Java/Scala/JavaScript/TypeScript/Python.
Proficiency in Linux/Unix environments.
Experience with databases technologies (relational, NoSQL, property graph, RDF/triple store).
Self-motivated, proactive and excellent in communication skills.
Ideal Candidate Will Have
Experience with cheminformatics toolkits (e.g., OpenEye, CDK, RDKit) is plus.
Experience with big data technology stack (Hadoop, Spark, HDFS, EMR, Glue).
Experience with AWS DevOps tools (CodeCommit, Cloud Development Kit, CDK Pipeline).
Experience with Databricks/SageMaker/DataRobot, MLFlow or other ML and MLOps tools.
Experience with Neo4j and graph analytics.
Experience building applications using AWS Serverless technologies such as Lambda, SQS, Fargate, DynamoDB, S3.
Experience with Generative AI, LLMs, and prompt engineering.
Overseas experience in working arrangements - working with teams off continent (e.g., N. America, Europe, etc.)
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