The Center of Excellence (CoE) in Data Science and Bioinformatics at LabCorp Information Technology department applies various data science disciplines (including artificial intelligence, machine learning, graph databases, statistics, bioinformatics, and natural language processing) to our clinical, operational and financial challenges, and creates opportunities to enhance the value of our offerings to our customers. Additionally, it integrates the data sciences and bioinformatics efforts between the LabCorp diagnostics and drug development units and serves as a collaboration platform to foster teamwork and learning throughout the LabCorp IT organization.

The internship program in this CoE provide a unique opportunity for the students to interact with the CoE personnel and get hands-on experience and knowledge of solving real life problems in data sciences and bioinformatics. It also contributes directly to LabCorp research and development efforts to address challenging data science issues and speed up critical production development efforts. Interns typically work on specific bioinformatics projects under the guidance of CBI members.

• Analysis of SARS-Cov-2 viral genomes samples from all over the USA to get insights into the spread of the pandemic
• Research and develop next generation sequencing (NGS) analysis for Labcorp's existing and novel laboratory tests. Typical projects would include developing pipeline to integrate the role of non-coding variants in disease or develop new Human Leukocytes Antigen (HLA) allele typing pipelines for transplant samples
• Research and Development of Labcorp's microbiome offerings, particularly, bioinformatics analysis pipeline
• Copy Number Variation (CNV) Algorithm Bakeoff Project: Evaluate the performance of these tools to identify the best one to incorporate into the genetic tests offered by Labcorp
• Data mining and predictive modeling of diseases using the laboratory test data on over half the US population
• Using machine learning and AI to develop disease prediction models for various common and rare disease such as CKD and asthma
• Application of novel genomics and bioinformatics tools to better characterize the Human Leukocytes Antigen (HLA) alleles and apply it to improve survival rates in transplantation.
• Hybrid On-Premise-Cloud Bioinformatics Workflow: Develop a workflow that seamlessly integrates the results of analysis carried out in the cloud with those generated in-house

• Pursuing a BS, MS, or Ph.D. degree in computer science, bioinformatics or related discipline
• Enjoy solving problems; inquisitive and analytical; engaged and motivated
• Able to work both independently and as part of a larger team
• Ability to see the big picture and work towards that goal
• Basic understanding of genomics and biology
• Familiarity with genomics related files and formats such as fastq file, a BAM file and a VCF file
• Experience in artificial intelligence and statistical learning
• Experience with statistical methodologies and machine learning techniques such as: neural networks, graphical models, ensemble methods and natural language processing
• Experience with multiple deep learning techniques such as CNN, LSTM, RNN, etc., in addition to standard machine learning approaches such as those found in scikit-learn.
• Master of evaluation techniques for supervised and unsupervised techniques. Knows to evaluate the quality of data and determine gaps in data or assumptions.
• Proficiency with Python or R. Can develop meaningful python code using objective oriented programming and functional programming. Writes tests for code. Can debug errors quickly.
• Strong data visualization skills.
• Familiarity with one or more machine learning libraries or frameworks such as: PyTorch, Tensorflow.
• Experience with rational and non-structure databases is highly desirable.
• Experience using cloud technologies such as AWS with tools such as S3, EC2, Lambda, Athena, etc.
• Demonstrated success in technical proficiency, scientific creativity, collaboration with others and independent thought.
• Ability to collaborate with the team and translate existing research into practical solutions and products ability to build and manage relationships with various collaborators across and outside the company.
• Comfortable working with both technical and non-technical staff to translate concepts and algorithms into working prototypes.
• Drive project execution and implement a robust plan for measuring success
• Lead discussions with senior leadership at the department or functional level