CCL Home Page
Up Directory CCL 20.06.25 Computational Scientist, ML, Pfizer, Cambridge, MA
From: jobs at (do not send your application there!!!)
To: jobs at
Date: Tue Jun 30 13:58:43 2020
Subject: 20.06.25 Computational Scientist, ML, Pfizer, Cambridge, MA
The Pfizer Simulation and Modeling Sciences (SMS) group has an opening 
for a computational methods developer with strong expertise in 
computational biology, bioinformatics, Artificial Intelligence (AI) and 
Machine Learning (ML). Working with the biotherapeutics group, 
the successful candidate will leverage skills in sequence analysis, 
protein structure modeling, machine learning, and scientific programming 
to develop AI models and computational tools that enable design of 
antibody therapeutics and prediction of biophysical and therapeutic 
properties. To be successful in this role, the incumbent must be able 
to effectively collaborate with colleagues with diverse scientific 
background, identify problems and opportunities, and combine techniques 
from computational biology and AI, in particular recent advances in deep 
learning, to rapidly develop powerful computational solutions.

Identify novel and creative applications of deep learning 
approaches to advance discovery and development of antibody therapeutics.

Collaborate across biotherapeutics organization to implement powerful AI 
models and cutting-edge computational tools to enable rapid developability 
assessment of novel monoclonal antibodies.

Effectively utilize relevant public and proprietary databases and 
available computational resources (internal HPC and Cloud) to develop 
ML models to predict important biophysical and therapeutic properties 
of antibodies.

Occasionally contribute to the ongoing and new ML-related efforts within 
SMS in the area of small molecule discovery and development.

Leverage proprietary computational framework and applications to deploy 
AI/ML models for wide usage by Pfizer scientists.

Proactively identify, assess, and internalize promising methods and tools.

Communicate and explain computational models and ML techniques to 
broad scientific audience from diverse discipline.

Ph.D. in computational biology, chemical engineering, computer science, 
physical or biological sciences, machine learning, or related discipline.

Experience with several machine learning algorithms (e.g. Random Forest, 

Support Vector Machine, Deep Neural Networks) and packages (e.g. Sci-kit 
Learn, Keras, TensorFlow, PyTorch).

Track record of applying machine learning, in particular modern deep 
learning approaches, to solve relevant biological problems.

Familiarity with concepts, techniques, and common tools used for sequence 
analysis and protein structure modeling.

Experience with Unix/Linux, HPC environments, and high-level programming 
language (e.g. Python).

Excellent communication and interpersonal skills.

Demonstrated track record of applying AI/ML, in particular cutting-edge 
deep learning techniques such as ConvNet, RNN, generative modeling, and 
reinforcement learning to tackle complex drug discovery and development 

Experience in applying ML to immunology data, e.g. HLA peptide binding.

Last Date to Apply for Job: July 17, 2020
Eligible for Employee Referral Bonus
All @ signs were changed to * to fight spam. Before you send e-mail, you need to change * to @
For example: change joe * to
Please let your prospective employer know that you learned about the job from the Computational Chemistry List Job Listing at If you are not interested in this particular position yourself, pass it to someone who might be -- some day they may return the favor.
Modified: Tue Jun 30 18:32:09 2020 GMT
Page accessed 1412 times since Thu Jun 25 21:12:45 2020 GMT