Company DescriptionAt Biogen, our mission is clear - we are pioneers in neuroscience. Biogen discovers, develops, and delivers worldwide innovative therapies for people living with serious neurological and neurodegenerative diseases. Together, our employees create, commercialize, and manufacture transformative therapies for our patient population. We at Biogen are committed to building on our culture of inclusion and belonging that reflects the communities where we operate and the patients who we serve. We are focused on strengthening our foundation to advance our overall Diversity, Equity and Inclusion (DE&I) strategy and, most importantly, ensure all our employees feel included.As an intern or co-op at Biogen, you can expect to be placed on a real project, under the guidance of experienced professionals and subject matter experts who are invested in your career and academic growth. We also ensure that you have plenty of opportunities to build your network, learn more about our organization through weekly lunch and learns led by leaders from across the company, and join us for several fun events.Job DescriptionThis application is for a 12-week internship role from June - August 2022. Resume review begins in January 2022. The Biostatistics Department in the Analytics and Data Sciences organization provides statistical support across Research and Development. The clinical statisticians in the biostatistics group collaborate with stakeholders from different disciplines to develop agile and robust clinical development plans and decision frameworks for portfolio of products encompassing early and late-stage development. They also provide statistical expertise and manage the activities for clinical programs to ensure valid and efficient study designs. For this role within Neuromuscular DU, we aim to investigate and develop practical methods in AI and ML for neuromuscular disease development.  Position DescriptionAs an intern, you will investigate and develop practical methods in AI and ML for ALS clinical development. Applications might include the development of enrichment criteria for patient pre-selection (in post hoc manner), as well as the prediction of individual treatment outcome. Clustering, classification, and feature importance analysis will be explored to identify the subgroup of patients that are more likely to respond to the drug. Clinical data, biomarker data, as well as other available related data source will be combined to build a predictive model for individual treatment outcome.ImplementationsLiterature search for recent application of AI/ML in clinical trial development. Explore data from various BIIB067 studies and other internal/external ALS studies. Apply AI/ML methodologies to identify the subgroup of patients that benefit from the drug using various clustering/classification algorithms (e.g. K-means, SVM, hierarchical clustering, mean shift clustering, decision tree, neural network algorithms etc) and various feature importance strategies (e.g. R2 loss, partial dependence (PDP) and accumulated local effects (ALE) plots, local interpretable model-agnostic explanations (LIME), Shapley additive explanations (SHAP) etc). Build predictive model for individual treatment outcome by integrating clinical data, biomarker data, and other related data source via various statistical/AI/ML models (e.g. mixed model, tree based model, neural network model etc). Evaluate the results from these modeling via cross validation by partitioning data into training data and test data. The Personalized European Network for the Cure of ALS (ENCALS) survival prediction model for ALS allows a reliable estimate of survival at diagnosis (i.e. personalized prognosis). The importance/significance of predictions from ENCALS survival prediction model in subgroup identification and treatment outcome prediction will also be explored. QualificationsTo participate in the Biogen Internship Program, students must meet the following eligibility criteria:Legal authorization to work in the U.S. At least 18 years of age prior to the scheduled start date Be currently enrolled in an accredited college or university Education Enrolled in PhD program in statistics, biostatistics, or related field. Masters degree required. Additional InformationAll your information will be kept confidential according to EEO guidelines.