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Job Description

_Objective / Purpose:_

+ A new position within the Biologics Engineering & Antibody Discovery team of Global Biologics, this role requires an experienced, self-motivated and driven scientist who can positively impact the pipeline through engineering and optimization of therapeutic candidates from _in vitro_ and _in vivo_ platforms, while working closely with the ML/computational team.

+ Depth of understanding of antibody engineering for design, optimization, and engineering utilizing structure-function relationships and molecular modelling while predicting behaviors.

+ Design and execution of optimization of molecules for properties such as affinity, potency, stability, specificity, stability, PK. May work on multiple programs in parallel. Formats to include monoclonal, single domain antibodies (VHH, VH), and multispecific antibodies. Deep understanding of antibody structure and function, as well as biologics discovery processes.

+ Effective communication with the NGS and computational teams to best optimize

+ The role requires excellent technical knowledge of antibody engineering and coding using python and optimization tools

+ A critical element of the role is recognizing and streamlining the most efficient ways of working. The role requires tremendous drive, and motivation to deliver (and beat) team and program goals, while also pushing the boundaries to enhance discovery and optimization.

+ Analysis, interpretation and communication of results, with proactive advice and next steps within the local and broader teams

_Accountabilities:_

+ Accountable for the successful and highly efficient design, test, and analysis lead optimization of antibody/single domain molecules meeting candidate profiles within programs

+ Deeply involved with the _in vitro_ and _in vivo_ teams, proactive in interpreting and connecting multiparametric datasets, sequences, and structures to swiftly enable the feedback loop of optimization.

+ Deeply involved in programs, wholly aware of the candidate goals. As such, leads antibody design and maturation efforts.

+ Full proficiency in python language for extraction and implementation of latest tools from GitHub and well versed in tools in biologics engineering not limited to MOE, Schrodinger, Rosetta, ImmuneBuilder, AntiFold and others. Combines this knowledge for the design of smaller and larger sets of in silico focused libraries to enhance lead candidate properties.

+ Applies knowledge of antibody repertoire analysis, sequence (OAIS, Nanobody database ) and structural database (PDB, AF2, Uniport) and others,

+ Member of the _antibody engineering_ team, sharing updates, and findings with the wider team for full dynamic response to data. Ability to flex in strategies and workflows accordingly driving for desired outcome. Works well within a team setting, takes on advice and take proactive steps to problem-solve

+ Thoroughly documents experiments with LIMS systems, and communicates results within the BEAD team and cross-functional project teams.

+ Is highly efficient in time management and sharing changes, plans specifics of project-related work with oversight from manager or project representative.

+ Troubleshoots and initiates routine problem investigation and recommends solutions to meet objectives.

+ Excellent basic knowledge of science/technology outside biologics discovery and engineering, pro-actively sharing knowledge and learnings from cross-functional background and programs

_Education & Competencies (Technical and Behavioral):_

+ PhD in a scientific discipline (or equivalent) with 2+ years relevant experience, or MS with 8+ years relevant experience, or BSc. With 10+ years of relevant experience

+ Need to have a proven track record of excellent problem-solving, antibody engineering and lead optimization as demonstrated by publications or oral/poster presentations.

+ Full proficiency in python language for extraction and implementation of latest tools from GitHub and well versed in tools in biologics engineering not limited to MOE, Schrodinger, Rosetta, ImmuneBuilder, AntiFold and others.

+ Experience with machine learning approaches is nice to have, and their application to biological problems, and familiarity with statistical modeling and data visualization

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.

For Location:

Boston, MA

$137,000.00 - $215,270.00

The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location.

EEO Statement

_Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law._

Locations

Boston, MA

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

Job Exempt

Yes

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.